Type:	Package
Version:	2.1.9
Date:	2025-06-27
Title:	Interactive Analytic Networks
Description:	Create interactive analytic networks. It joins the data analysis power of R to obtain coincidences, co-occurrences and correlations, and the visualization libraries of 'JavaScript' in one package.
License:	GPL-2 | GPL-3
Depends:	R (≥ 3.5.0)
Imports:	rD3plot (≥ 1.1.37), igraph (≥ 1.0.1), Matrix (≥ 1.2-4), haven (≥ 1.1.0), MASS (≥ 7.3), GPArotation(≥ 2022.4), methods
Suggests:	knitr, rmarkdown, lavaan, shiny, htmltools, openxlsx, data.table, readr
VignetteBuilder:	knitr
NeedsCompilation:	no
Maintainer:	Modesto Escobar <modesto@usal.es>
URL:	https://modesto-escobar.github.io/netCoin-2.x/
Encoding:	UTF-8
BugReports:	https://github.com/Modesto-Escobar/netCoin-2.x/issues
Acknowledgments:	Grants CSO2013-49278-EXP, PGC2018-093755-B100, PDC2022-133355-100, PID2023-147358NB-100 funded by MICIU/AEI/10.13039/501100011033 and by “European Union NextGenerationEU/PRTR”.
Packaged:	2025-07-03 20:26:49 UTC; modes
Author:	Modesto Escobar [cre, aut, cph], David Barrios [aut], Carlos Prieto [aut], Luis Martinez-Uribe [aut], Pablo Cabrera-Álvarez [aut], Cristina Calvo-López [aut]
Repository:	CRAN
Date/Publication:	2025-07-03 21:10:01 UTC

The netCoin package.

Description

Create interactive networked coincidences. It joins the data analysis power of R to study coincidences and the visualization libraries of JavaScript in one package.

Details

Coincidence analysis detects what events, characters, objects, attributes, or characteristics tend to occur together within certain limits.

These given limits are call scenarios (S) and are considered to be the units of analysis, and as such they have to be placed in the rows of a matrix or data.frame.

In each i scenario, a series of J events X_j, which are to be represented as dichotomous variables X_{j} in columns, may occur (1) or may not occur (0). Scenarios and events constitute an incidence matrix (I).

Incidence matrix

From this incidences matrix, a coincidence (C) matrix can be obtained with the function coin. In this matrix the main diagonal represents frequencies of X_j, while the others elements are number of coincidences between two events.

Coincidence matrix

Once there is a coin object, a similarity matrix can be obtained. Similarity matrices available in netCoin are:

• Matching (m), Rogers & Tanimoto (t) Gower (g) Sneath (s) and Anderberg (and).

• Jaccard (j), dice (d), antiDice (a), Ochiai (o) and Kulczynski (k).

• Hamann (ham), Yule (y), Pearson (p), odds ratio (od) and Rusell (r).

Other measures that can be obtained from coin are:

• Relative frequencies (x), conditional frequencies (i) coincidence degree (cc) and probable degree of coincidence (cp).

• Haberman (h) and Z value of Haberman (z)

To obtain similarity and other measures matrices, the function sim elaborates a list of them.

Similarity matrix

edgeList makes a collecion of edges composed by a list of similarity measures whenever a criterium (generally p(Z)<.50) is met.

Edge list

In order to make a graph, two data frames are needed: a nodes data frames with names and other nodes attributes (see asNodes) and an edge data frame (see edgeList). For more information go to netCoin.

Author

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

References

Escobar, M. (2009): "Redes Semanticas en Textos Periodisticos: Propuestas Tecnicas para su Representacion", en Empiria, 17, 13-39.

Escobar, M.(2015): "Studying Coincidences with Network Analysis and Other Multivariate Tools", in The Stata Journal, 15(4), 1118-1156.

Escobar, M. and J. Gomez Isla (2015): "The Expression of Identity through the Image: The Photographic Archives of Miguel de Unamuno and Joaquin Turina", en Revista Espanola de Investigaciones Sociologicas, 152, 23-46.

Data: Finches' presence in Galapagos Islands.

Description

Data frame with absence(0) presence(1) of finches in the Galagos Islands.

Usage

data("Galapagos")

Format

A data frame with 17 localizations (islands) and 13 variables (Genus and species of the finches):

Geospiza magnirostris

Geospiza fortis

Geospiza fuliginosa

Geospiza difficilis

Geospiza scandens

Geospiza conirostris

Camarhynchus psitticula

Camarhynchus pauper

Camarhynchus parvulus

Platyspiza crassirostris

Cactospiza pallida

Cactospiza heliobates

Certhidea olivacea

References

Sanderson, James (2000). Testing Ecological Patterns: A Well-known Algorithm from Computer Science Aids the Evaluation of Species Distributions. American Scientist, 88, pp. 332-339.

Examples

data(Galapagos)
head(Galapagos,10)

Adds a description to a 'netCoin' object.

Description

addDescription adds a description to a 'netCoin' object.

Usage

addDescription(x, description)

Arguments

Value

A 'netCoin' object.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca.

Examples

data(finches)
data(Galapagos)

Net<-allNet(Galapagos,nodes=finches, criteria="hyp", maxL=.05,
        lwidth ="Haberman",lweight="Haberman",
        size="frequency", color="species", layout="mds",
        main="Species coincidences in Galapagos Islands",
        note="Data source: Sanderson (2000)")

img <- system.file("extdata", "p.Crassirostris.png",
        package="netCoin")
Net <- addDescription(Net,"Species coincidences in Galapagos Islands")

## Not run: 
multi <- multigraphCreate(Network=Net)
multiPages(multi,"Graph description example",show=TRUE)

## End(Not run)

Adds an image to a 'netCoin' object.

Description

addImage adds an image to a 'netCoin' object.

Usage

addImage(x, img)

Arguments

Value

A 'netCoin' object.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca.

Examples

data(finches)
data(Galapagos)

Net<-allNet(Galapagos,nodes=finches, criteria="hyp", maxL=.05,
        lwidth ="Haberman",lweight="Haberman",
        size="frequency", color="species", layout="mds",
        main="Species coincidences in Galapagos Islands",
        note="Data source: Sanderson (2000)")

img <- system.file("extdata", "p.Crassirostris.png",
        package="netCoin")
Net <- addImage(Net,img)

## Not run: 
multi <- multigraphCreate(Network=Net)
multiPages(multi,"Graph image example",show=TRUE)

## End(Not run)

Networked coincidences.

Description

addNetCoin changes netCoin object attributes.

Usage

addNetCoin(x, ...)

Arguments

Value

This function returns a netCoin object. If the 'dir' attribute is specified, the function creates a folder in the computer with an HTML document named index.html which contains the produced graph. This file can be directly opened with your browser and sent to a web server to work properly.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

References

Escobar, M. and Martinez-Uribe, L. (2020) Network Coincidence Analysis: The netCoin R Package. Journal of Statistical Software, 93, 1-32. doi:10.18637/jss.v093.i11.

Examples

# A character column (with separator)
frame <- data.frame(A = c("Man; Women", "Women; Women",
                        "Man; Man", "Undet.; Women; Man"))
data <- dichotomize(frame, "A", sep = "; ")[2:4]
C <- coin(data) # coincidence matrix
N <- asNodes(C) # node data frame
E <- edgeList(C) # edge data frame
net <- netCoin(N, E) # netCoin object
net <- addNetCoin(net, color="frequency") # netCoin object with color applied to nodes

Adds a tutorial for the gallery.

Description

addTutorial adds a tutorial for a gallery.

Usage

addTutorial(x, image = NULL, description = NULL)

Arguments

Value

Object of class gallery_rd3.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca.

Examples

data("finches")
finches$species <- system.file("extdata", finches$species,
        package="netCoin") # copy path to the species field
g <- gallery(finches, image="species", main="Species in Galapagos Islands",
        note="Data source: Sanderson (2000)")

g <- addTutorial(g, 
  description="Here you can see different finches species in Galapagos islands.")

## Not run: 
plot(g)

## End(Not run)

Networked coincidences from incidences data.

Description

allNet produces a network object of coincidences from a data frame or a matrix with dichotomous values.

Usage

allNet(incidences, weight = NULL, subsample = FALSE, pairwise = FALSE,
       minimum=1, maximum = nrow(incidences), 
       sort = FALSE, decreasing = TRUE,
       frequency = FALSE, percentages = TRUE, 
       procedures = "Haberman", criteria = "Z", Bonferroni = FALSE,
       support = -Inf, minL = -Inf, maxL = Inf,
       directed = FALSE, diagonal = FALSE, 
       sortL = NULL, decreasingL = TRUE,
       igraph = FALSE, dir=NULL, ...)

Arguments

Details

Possible measures in procedures are

• Frequencies (f), Relative frequencies (x), Conditional frequencies (i), Coincidence degree (cc), Probable degree (cp),

• Expected (e), Confidence interval (con)

• Matching (m), Rogers & Tanimoto (t), Gower (g), Sneath (s), Anderberg (and),

• Jaccard (j), Dice (d), antiDice (a), Ochiai (o), Kulczynski (k),

• Hamann (ham), Yule (y), Pearson (p), odds ratio (od), Rusell (r),

• Haberman (h), Z value of Haberman (z),

• Hypergeometric p greater value (hyp).

• Convert a matrix into an edge list (shape).

Value

This function creates a netCoin object (or igraph) and, if stated, a folder in the computer with an HTML document named index.html which contains the produced graph. This file can be directly opened with your browser and sent to a web server to work properly.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

References

Escobar, M. and Martinez-Uribe, L. (2020) Network Coincidence Analysis: The netCoin R Package. Journal of Statistical Software, 93, 1-32. doi:10.18637/jss.v093.i11.

Examples

# A character column (with separator)
frame <- data.frame(A = c("Man; Women", "Women; Women",
                        "Man; Man", "Undet.; Women; Man"))
data <- dichotomize(frame, "A", sep = "; ")[2:4]
allNet(data) # network object

Images in a grid gallery.

Description

asGallery produces a gallery_rd3 object.

Usage

asGallery(net)

Arguments

Value

Object of class gallery_rd3.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

data("Galapagos")
data("finches")
finches$species <- system.file("extdata", finches$species,
        package="netCoin") # copy path to the species field
Net <- allNet(Galapagos, nodes=finches, criteria="hyp", maxL=.05,
        image="species",
        main="Species coincidences in Galapagos Islands",
        note="Data source: Sanderson (2000)")
gallery <- asGallery(Net)

Nodes data frame.

Description

Nodes data frame from either an edge list or a coin object.

Usage

asNodes(C, frequency = TRUE, percentages = FALSE, language = c("en","es","ca"))

Arguments

Value

A data frame with nodes' names and their frequency and/or percentages if the input is a coin object

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

References

Escobar, M. and Martinez-Uribe, L. (2020) Network Coincidence Analysis: The netCoin R Package. Journal of Statistical Software, 93, 1-32. doi:10.18637/jss.v093.i11.

Examples

# From a random incidence matrix I(25X4)
I <- matrix(rbinom(100, 1, .5), nrow = 25, ncol = 4,
     dimnames = list(NULL, c("A", "B", "C", "D")))
C <- coin(I)
asNodes(C)

Networked coincidences.

Description

barCoin produces a barCoin object.

Usage

barCoin(data, variables = colnames(data), commonlabel = NULL,
        dichotomies = c("_all","_none"), valueDicho = 1, weight = NULL,
        subsample = FALSE, sort = NULL, decreasing = TRUE, nodes = NULL,
        name = NULL, select = NULL, scalebar = FALSE, note = NULL, 
        label = NULL, text = NULL, color = NULL, defaultColor = "#1f77b4", 
        expected = FALSE, confidence = FALSE, level = .95, significance = FALSE, 
        minimum = 1 , maximum = nrow(data), percentages = FALSE, 
        criteria = c("Z","hyp"), Bonferroni = FALSE, 
        support = 1, minL = -Inf, maxL = 1,
        language = c("en","es","ca"), cex = 1.0, dir = NULL)

Arguments

Value

Object of class barCoin.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

# A character column (with separator)
frame <- data.frame(A = c("Man; Women", "Women; Women",
                        "Man; Man", "Undet.; Women; Man"))
data <- dichotomize(frame, "A", sep = "; ")[2:4]

barCoin(data,dichotomies="_all")
barCoin(data,dichotomies="_all",confidence=TRUE,percentages=TRUE)

Categorize a network

Description

This function calculates the centrality measures of a network.

Usage

calCentr(graph,
  measures = c("degree","wdegree","closeness","betweenness","eigen"),
  order = "")

Arguments

Details

This function reproduces some of the most significant classic Social Network Theory's centrality measures. See Wasserman (1994), Freeman (1978), or Bonacich & Lloyd (2001) to know more.

a) Degree = Degree centrality is measured by the total amount of direct links with the other nodes.

b) Closeness = Closeness centrality is meant to measure one node to the others nodes' sum distances

c) Betweenness = Betweenness centrality measures one node undertaking "mediation" role in a network.

d) Eigen = Eigenvector centrality measures a node's importance while giving consideration to the importance of its neighbors.

By default, measures = "all", thus all the measures will be calculated. The function can be applied to an igraph or a netCoin object. In case the graph is undirected, it will show the degree, weighted degree, closeness, betweeness and eigen degree. Moreover, if it us directed, it will show the indegree, windegree and outdegree, both weighted and unweighted (See example.).

Value

This function creates a list containing two elements: 1) a data.frame (nodes) with all the centrality measures applied to the graph and 2) another data.frame (graph) with this measures applied to the whole network.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

# A character column (with separator)
frame <- data.frame(A = c("Man; Women", "Women; Women",
                        "Man; Man", "Undet.; Women; Man"))
data <- dichotomize(frame, "A", sep = "; ")[2:4]
C <- coin(data) # coincidence matrix
N <- asNodes(C) # node data frame
E <- edgeList(C) # edge data frame
G <- netCoin(N, E, showArrows=TRUE) # netCoin object
calCentr(G, "all")

Produce interactive multi graphs.

Description

caring produce an interactive multi graph from caring arguments.

Usage

caring(filepath,arguments)

Arguments

Value

This function returns a mGraph object. The function creates a folder in your computer with an HTML document named index.html which contains the graph. This file can be directly opened with your browser.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca.

Examples

## Not run: 
filename <- "demo.sav"
arguments <- list(
  variables = c("Gender", "Income category in thousands",
    "Primary vehicle price category"),
  plot = "network"
)
graph <- caring(filename,arguments)
plot(graph)

## End(Not run)

Produce interactive multi graphs.

Description

caring_create_graphs produce an interactive multi graph from caring arguments.

Usage

caring_create_graphs(data,arguments)

Arguments

Value

This function returns a mGraph object. The function creates a folder in your computer with an HTML document named index.html which contains the graph. This file can be directly opened with your browser.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca.

Examples

data <- data.frame(Gender=c(rep("Man",3),rep("Woman",3)),
                    Opinion=c("Yes","Yes","No","No","No","Yes"))
arguments <- list(
  variables = c("Gender", "Opinion"),
  dichotomies = "Opinion",
  valueDicho = "Yes",
  plot = c("surCoin","network")
)
graph <- caring_create_graphs(data,arguments)
## Not run: 
plot(graph)

## End(Not run)

Read sav, dta, xlsx, tsv and csv files.

Description

caring_read_file reads sav, dta, xlsx, tsv and csv files and prepares data for caring.

Usage

caring_read_file(filepath)

Arguments

Value

This function returns a data frame.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca.

Examples

## Not run: 
filename <- "demo.sav"
data <- caring_read_file(filename)

## End(Not run)

CobWeb graph (Upton).

Description

cobCoin produces a netCoin object to graph a CoWeb graphic (Upton 2000).

Usage

cobCoin(data, variables=names(data), degree=0, significance=.05, ...)

Arguments

Value

This function creates a netCoin object (or igraph) and, if stated, a folder in the computer with an HTML document named index.html which contains the produced graph. This file can be directly opened with your browser and sent to a web server to work properly.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

References

Upton, Graham J.G. (2000) Cobweb diagrams for multiway contingency tables. The Statistician, 49(1), 79-85.

Examples

# A data frame with two variables Gender and Opinion
frame <- data.frame(Gender=c(rep("Man",3),rep("Woman",3)),
                    Opinion=c("Yes","Yes","No","No","No","Yes"))
cobCoin(frame, significance=.5, degree=45) # netCoin object

# A data frame with two variables (Gender and Hand) and nodes
input <- data.frame(
  Gender = c("Women", "Men", "Men", "Women", "Women","Men",
             "Men", "Men", "Women", "Women", "Men", "Women"),
  Hand   = c("Right", "Left","Right", "Right", "Right", "Right",
             "Left", "Right", "Right", "Left","Right", "Right"))
nodes <- data.frame(
  name  = c("Gender:Men","Gender:Women", "Hand:Left", "Hand:Right"),
  label = c("Women(50\u25)","Men(50\u25)",
            "Left hand(25\u25)", "Right hand(75\u25)"))
G <- cobCoin(input, nodes=nodes, label="label", degree=22.5,
             showArrows=TRUE, significance=1)

coexist Interactive network of time coexistences of periods.

Description

coexist produces interactive graphs representing coexistence. Two periods or lifes coexist if they share a given number of years.

Usage

coexist(periods, name="name", start="start", end="end", 
        fields=names(periods), plusstart=0, minusend=0, igraph=FALSE, ...)

Arguments

Details

Two periods coexists if they have at least one year in common. Periods can be trimmed at the begining or at the end.

Value

This function creates a netCoin object (or igraph) and, if plotted, a folder in the computer with an HTML document named index.html which contains the produced graph. This file can be directly opened with your browser and sent to a web server to work properly.

A netCoin object has three elements:

Note

Periods could be the life of people, in whose case start is their birth and end their death year.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

See Also

timeCoin and dyncohort

Examples

# With sociologists data.
data(sociologists)
# Produce an igraph object:
coexist(sociologists, start="birth", end="death", igraph=TRUE)
# Omit as coexistence the 15 firts years of life:
sociologists$picture <- system.file("extdata", sociologists$picture,
        package="netCoin") # copy path to the picture field
coexist(sociologists, start="birth", end="death", plusstart=15, image="picture", imageName="name")

Coincidence matrix.

Description

A coin object is a squared matrix of coincidences with its names and the frequency of events as attributes.

Usage

coin(incidences, minimum = 1, maximum = nrow(incidences),
     sort = FALSE, decreasing = TRUE, 
     total = FALSE, subsample = FALSE,
     weight = NULL, pairwise = FALSE)

Arguments

Details

Produce a matrix of coincidences from a matrix of incidences.

Value

An object of coin class

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

References

Escobar, M. and Martinez-Uribe, L. (2020) Network Coincidence Analysis: The netCoin R Package. Journal of Statistical Software, 93, 1-32. doi:10.18637/jss.v093.i11.

Examples

## Random incidence matrix: 25 scenarios, 4 events.
I <- matrix(rbinom(100, 1, .5), nrow = 25, ncol = 4,
            dimnames = list(NULL, c("A", "B", "C", "D")))
coin(I, sort = TRUE)

## Hair by Eye by Sex table from M. Friendly (2000)
data(HairEyeColor)
H<-as.data.frame(HairEyeColor)
W<-H$Freq
I<-dichotomize(H,c("Hair","Eye","Sex"),add=FALSE)
coin(I,w=W)

Coocurrence matrix.

Description

A coocurrence object consists of a matrix with the number of ocurrences in its main diagonal and the number of coocurrences outside this diagonal. Besides, this object has two attributes: 1) n is the total of the sum of the ocurrences in each row.2) m is the sum of the maximum number of ocurrences in each row.

Usage

coocur(ocurrences, minimum = 1, maximum = Inf,
       sort = FALSE, decreasing = TRUE)

Arguments

Details

Produce a matrix of coocurrences from a matrix of occurences.

Value

An object of cooc class with a coocurrence matrix. It has two attributes:

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

## Tossing two coins five times.
D<-data.frame(Head=c(2,1,1,0,2),Tail=c(0,1,1,2,0))
coocur(D)

Dynamic networked correlations.

Description

netCorr produces a network object of dynamic correlations. Its input has to be at least one set of quantitative variables.

Usage

d_netCorr(variables, nodes = NULL, weight=NULL, 
        pairwise=FALSE, minimum=-Inf, maximum=Inf,
        frequency=FALSE, means=TRUE, 
        method=c("pearson", "kendall", "spearman"), criteria="value", Bonferroni=FALSE,
        minL=0, maxL=Inf,
        sortL=NULL, decreasingL=TRUE,
        factorial=c("null", "pc", "nf", "vf", "of"),
        components=TRUE, backcomponents=FALSE,
        sequence=seq(.20, 1, .01), textFilter=c(1, .99), speed=50,
        dir=NULL, ...)

Arguments

Value

The function creates a list object to create a multigraph and eventually a folder in the computer with an HTML document named index.html which contains the produced dynamic graphs. This file can be directly opened with your browser and sent to a web server to work properly.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

# A character column (with separator)
data(iris)
d_netCorr(iris[,1:4],ltext="value", sequence=seq(.80, 1, .05), zoom=3, textFilter=.85,
 main="Correlations between measurements of Iris Species", components=FALSE,
 note="Anderson, Edgar (1935) y Fisher, R. A. (1936)") # network object

Data: Roll a die (100 times).

Description

Data frame with events as result.

Usage

data("dice")

Format

A data frame with 100 observations (scenarios) on the following 11 variables (events):

dice

: a numeric vector, representing dice results

1

: a dichotomous vector of the elemental event "1"

2

: a dichotomous vector of the elemental event "2"

3

: a dichotomous vector of the elemental event "3"

4

: a dichotomous vector of the elemental event "4"

5

: a dichotomous vector of the elemental event "5"

6

: a dichotomous vector of the elemental event "6"

odd

: a dichotomous vector of odd events

even

: a dichotomous vector of even events

small

: a dichotomous vector of small number events

large

: a dichotomous vector of large number events

Source

Random extraction via sample(1:6,100,replace=TRUE)

References

See events.

Examples

data(dice)
head(dice,10)

Dichotomize.

Description

This converts factor(s) o character(s) column(s) of a data frame into a set of dichotomous columns. Their names will correspond to the labels or text of every category.

Usage

dichotomize(data, variables,
            sep = "", min = 1, length = 0, values = NULL,
            sparse = FALSE, add = TRUE, sort = TRUE, nas = "None")

Arguments

Value

A data frame composed by the original plus the added dichotmous columns.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca, and Luis Martinez Uribe, Fundacion Juan March. See https://sociocav.usal.es/blog/modesto-escobar/

References

Escobar, M. and Martinez-Uribe, L. (2020) Network Coincidence Analysis: The netCoin R Package. Journal of Statistical Software, 93, 1-32. doi:10.18637/jss.v093.i11.

Examples

# A character column
frame1 <- data.frame(A = c("Man", "Women", "Man", "Undet."))
dichotomize(frame1, "A", sep = "; ")

# A character column (with separator)
frame2 <- data.frame(A = c("Man; Women", "Women; Women",
                         "Man; Man", "Undet.; Women; Man"))
dichotomize(frame2, "A", sep = "; ")

# A character column and another factor column (same sepatator)
frame3 <- data.frame(A = c("Man; Women", "Women; Women",
                         "Man; Man", "Undet.; Women; Man"),
                     C = factor(c(1:4), labels = c("Paris", "New York",
                         "London; New York", "<NA>")))
dichotomize(frame3, c("A", "C"), sep = "; ")

# A set of simple character or factor (same levels) variables. 
# In this case, you must use "C" separator.
frame4 <- data.frame(A = c("Man", "Women","Man", "Undet",NA),
                     B = c("Women","Women","Man","Women",NA),
					 C = c(NA,NA,NA,"Man",NA))
dichotomize(frame4,c("A","B","C"), sep="C")

Distance matrix.

Description

Convert a similarity matrix into a distance matrix.

Usage

distant(s, t = FALSE)

Arguments

Details

For better resultas, use the parameter distance in sim function.

Value

A distance matrix.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

# From a random incidence matrix I(25X4)
I <- matrix(rbinom(100, 1, .5), nrow = 25, ncol = 4,
     dimnames = list(NULL, c("A", "B", "C", "D")))
J <- sim(I, "Jaccard")
distant(J, t = TRUE)
#Same results
sim(I, "Jaccard", distance = TRUE)

Interactive graphs of dynamic cohorts.

Description

dyncohort produces interactive graphs representing dynamic cohorts. Two periods or lifes belongs to the same cohort if there are a difference of years in their start less or equal to a given number. In case of people's life, 15 or 25 are appropiate quantities to set. If year is equal to 0, a cohort is defined a those periods or lifes that begin at the same year.

Usage

dyncohort(periods, name="name", start="start", fields=names(periods), 
          years=0, igraph=FALSE, ...)

Arguments

Value

This function creates a timeCoin object (or igraph) and, if plotted, a folder in the computer with an HTML document named index.html which contains the produced graph. This file can be directly opened with your browser and sent to a web server to work properly.

A netCoin object has three elements:

Note

Periods could be the life of people, in whose case start is their birth year.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

See Also

timeCoin and coexist

Examples

# With sociologists data.
data(sociologists)
dyncohort(sociologists, start="birth")
# Condider 15 year dynamic cohort:
sociologists$picture <- system.file("extdata", sociologists$picture,
        package="netCoin") # copy path to the picture field
dyncohort(sociologists, start="birth", year=15, image="picture", imageName="name")

Edge list.

Description

Convert a coincidence/similarity/distance matrix into an edge list form.

Usage

edgeList(data, procedures="Haberman", 
         criteria="Z", level=.95, Bonferroni=FALSE, 
         min=-Inf, max=Inf, support=-Inf, directed=FALSE, 
         diagonal=FALSE, sort=NULL, decreasing=TRUE, pairwise=FALSE)

Arguments

Details

Possible measures in procedures are

• Frequencies (f), Relative frequencies (x), Conditional frequencies (i), Coincidence degree (cc), Probable degree (cp),

• Expected (e), Confidence interval (con)

• Matching (m), Rogers & Tanimoto (t), Gower (g), Sneath (s), Anderberg (and),

• Jaccard (j), Dice (d), antiDice (a), Ochiai (o), Kulczynski (k),

• Hamann (ham), Yule (y), Pearson (p), odds ratio (od), Rusell (r),

• Haberman (h), Z value of Haberman (z),

• Hypergeometric p greater value (hyp).

• Convert a matrix into an edge list (shape).

Value

A data frame in which the two first columns are source and target. The rest of the columns are the different statistics explicited in funcs parameter.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

References

Escobar, M. and Martinez-Uribe, L. (2020) Network Coincidence Analysis: The netCoin R Package. Journal of Statistical Software, 93, 1-32. doi:10.18637/jss.v093.i11.

Examples

# From a random incidence matrix I(25X4)
I<-matrix(rbinom(100,1,.5),nrow=25,ncol=4,
dimnames=list(NULL,c("A","B","C","D")))
C<-coin(I)
edgeList(C)

Data: European Social Survey, Round-8.

Description

A sample size of 1,000 respondents from the European Social Survey, Round-8.

Usage

data("ess")

Format

A data frame with 1000 cases (respondents) and 5 variables:

Gender

Gender (factor vector): Female, Male.

Age

Age (recoded factor vector): 15-29, 30-30, 40-49, 50-59, 60-69, 70 and +.

Social participation

Social participation (factor vector): No, Yes.

Political participation

Political participation (factor vector): No, Yes.

cweight

cweight (numeric vector): Cases weight.

References

ESS Round 8: European Social Survey Round 8 Data (2016). Data file edition 2.1. NSD - Norwegian Centre for Research Data, Norway - Data Archive and distributor of ESS data for ESS ERIC. doi:10.21338/NSD-ESS8-2016.

Examples

data("ess")
head(ess,10)

Data: Attributes of the dice events.

Description

Data frame with the attributes of the events of dice.

Usage

data("events")

Format

A data frame with 10 observations on the following 4 variables:

name

: a factor vector with 10 levels

label

: a factor vector with 10 levels

frequency

: a numeric vector

type

: a factor vector with 2 levels

Source

data(dice); coin.dice<-coin(dice); asNodes(coin.dice)

References

See dice.

Examples

data(events)
events

Images in a grid gallery.

Description

exhibit produces an interactive image gallery (alternative display).

Usage

exhibit(nodes, name = NULL, label = NULL, subtitle = NULL, order = NULL,
  decreasing = FALSE, ntext = NULL,
  mainframeHeight = NULL, mainframeWidth = NULL,
  image = NULL, zoom = NULL, main = NULL, note = NULL,
  frequencies = FALSE, tutorial = FALSE, tableButton = FALSE, export = FALSE,
  colorScheme = 0, language = c("en", "es", "ca"), dir = NULL)

Arguments

Value

Object of class gallery_rd3.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

data("finches")
finches$species <- system.file("extdata", finches$species,
        package="netCoin") # copy path to the species field
exhibit(finches, image="species")

Expected list.

Description

Converts a coin object to a links data frame with coincidences and expected values.

Usage

expectedList(data, names = NULL, min = 1, confidence=FALSE)

Arguments

Value

A links data frame with coincidences and expected values.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

# A character column (with separator)
frame <- data.frame(A = c("Man; Women", "Women; Women",
                        "Man; Man", "Undet.; Women; Man"))
data <- dichotomize(frame, "A", sep = "; ")[2:4]
C <- coin(data) # coincidence matrix
expectedList(C) # edge data frame

Data: Italian families in the Renaissance.

Description

Data frame with the characteristics of powerful families of Renaissance Italy.

Usage

data("families")

Format

A data frame with 16 families (rows) and 6 characteristics.

name

Family's name

f.Marriages

number of marriage links

f.Business

number of business links

wealth

wealth's index

priorates

number of priorates on control

seat

At least priorate

Source

PADGETT, J. F. Y C. K. ANSELL (1993): "Robust Action and the Rise of the Medici, 1400-1434", in American Journal of Sociology, 98, 1259-1319. (http://www.jstor.org/stable/2781822)

Examples

data("families")
head(families)

Data: Finches'attributes in Galapagos islands.

Description

Data frame with events as result.

Usage

data("finches")

Format

A data frame with 13 observations (pinches) and 4 variables (name and characteristics):

name

: Genus and species of the finche

frequency

: number of islands where the finche can be found

type

: Genus of the finche

species

: name of the file containing the picture of the finche

References

Sanderson, James (2000). Testing Ecological Patterns: A Well-known Algorithm from Computer Science Aids the Evaluation of Species Distributions. American Scientist, 88, pp. 332-339.

Examples

data(finches)
head(finches,10)

Produce interactive networks from igraph objects.

Description

fromIgraph produce an interactive network from an igraph object.

Usage

fromIgraph(G, ...)

Arguments

Value

This function returns a netCoin object. If the 'dir' attribute is specified, the function creates a folder in the computer with an HTML document named index.html which contains the produced graph. This file can be directly opened with your browser and sent to a web server to work properly.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

References

Escobar, M. and Martinez-Uribe, L. (2020) Network Coincidence Analysis: The netCoin R Package. Journal of Statistical Software, 93, 1-32. doi:10.18637/jss.v093.i11.

Examples

g <- igraph::make_ring(10)
fromIgraph(g)

Images in a grid gallery.

Description

gallery produces an interactive image gallery.

Usage

gallery(nodes, name = NULL, label = NULL, color = NULL,
    border = NULL, ntext = NULL, info = NULL, infoFrame = c("right","left"),
    image = NULL, zoom = 1, itemsPerRow = NULL, main = NULL, note = NULL,
    showLegend = TRUE, frequencies = FALSE, labelTooltip = TRUE,
    cexTooltip = 1, help = NULL, helpOn = FALSE, tutorial = FALSE,
    description = NULL, descriptionWidth = NULL, roundedItems = FALSE,
    ntextctrl = FALSE, controls = 1:5, cex = 1, defaultColor = "#1f77b4",
    language = c("en", "es", "ca"), dir = NULL)

Arguments

Value

Object of class gallery_rd3.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

data("finches")
finches$species <- system.file("extdata", finches$species,
        package="netCoin") # copy path to the species field
gallery(finches, image="species", main="Species in Galapagos Islands",
        note="Data source: Sanderson (2000)")

Create an html panel for nodes from different items (for galleries).

Description

Create an html panel for nodes from different items (for galleries).

Usage

get_panel_template(data, title=NULL, description=NULL, img=NULL,
                   text=NULL, color="auto", cex=1, mode = 1)

Arguments

Value

a character vector of html formatted panel.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

## Not run: 
data("sociologists")
sociologists$picture <- system.file("extdata", sociologists$picture,
        package="netCoin")
sociologists$html <- get_panel_template(sociologists, title="name",
  description="birth_country",img="picture", text="school")
plot(gallery(sociologists, info="html"))

## End(Not run)

Create a drop-down vignette for nodes from different items (for galleries).

Description

Create a drop-down vignette for nodes from different items (for galleries).

Usage

get_template(
  data,
  title = NULL,
  title2 = NULL,
  text = NULL,
  img = NULL,
  wiki = NULL,
  width = 300,
  color = "auto",
  cex = 1,
  roundedImg = FALSE,
  mode = 1
)

Arguments

Value

a character vector of html formatted vignettes.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

## Not run: 
data("sociologists")
sociologists$picture <- system.file("extdata", sociologists$picture,
        package="netCoin")
sociologists$html <- get_template(sociologists, title="name",
  title2="birth_country", text="school",img="picture", mode=2)
plot(gallery(sociologists, ntext="html"))

## End(Not run)

Create a drop-down vignette for nodes from different items (for galleries).

Description

Create a drop-down vignette for nodes from different items (for galleries).

Usage

get_template2(data, title=NULL, title2=NULL, text=NULL, wiki=NULL)

Arguments

Value

a character vector of html formatted vignettes.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

## Not run: 
data("sociologists")
sociologists$html <- get_template2(sociologists, title="name",
  title2="birth_country", text="school")
plot(exhibit(sociologists, ntext="html"))

## End(Not run)

Regression Graphs

Description

produces a netCoin object from a set of glm regressions.

Usage

glmCoin(formulas, data, weights=NULL, pmax=.05, 
                    twotail=FALSE, showArrows=TRUE,
                    frequency = FALSE, percentage = TRUE, 
                    color="variable", lwidth="z.value", 
                    circle= NA, language=c("en","es","ca"),
                    igraph=FALSE, ...)

Arguments

Value

This function creates a netCoin object (or igraph) and, if stated, a folder in the computer with an HTML document named index.html which contains the produced graph. This file can be directly opened with your browser and sent to a web server to work properly.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

## Dobson (1990) Page 93: Randomized Controlled Trial :
counts <- c(18,17,15,20,10,20,25,13,12)
outcome <- gl(3,1,9)
treatment <- gl(3,3)
Dobson <- data.frame(counts=counts, outcome=outcome, treatment=treatment)
model <- "counts ~ outcome + treatment, poisson"
glmCoin(model,Dobson)

Time incidences.

Description

Convert a data frame with two numbers (normally a beginning year and end year) into an incidences matrix whose rows are the intermediate numbers, and whose columns are the content of the names column.

Usage

incTime(data, name = "name", beginning = "birth", end= "death")

Arguments

Value

A data frame in which the two first columns are source and target. The rest of the columns are sim.=(1+threshold-real difference) and dist.=(difference between numbers)

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

# From sociologists data
data("sociologists")
head(incTime(sociologists))[,1:5]

Produce a circle layout of any number of nodes.

Description

layoutCircle produces a circle layout of any number of nodes.

Usage

layoutCircle(N,nodes=seq_len(nrow(N)),deg=0,name=NULL)

Arguments

Value

This function returns the input data frame of nodes with the resulting layout applied.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

A <- data.frame(name=letters)

L <- layoutCircle(A,name="name")

netCoin(A,layout=L)

Produce a layout of any number of nodes.

Description

layoutGrid produces a grid layout of any number of nodes.

Usage

layoutGrid(N,string,name=NULL,byrow=FALSE)

Arguments

Value

This function returns the input data frame of nodes with the resulting layout applied.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

A <- data.frame(name=letters)

L <- layoutGrid(A,"a,b,c,d,e.f,g,h,i,j.k,l,m,n,o,p.q,r,s,t,u.v,w,x,y,z","name")

netCoin(A,layout=L)

Data: Links between Italian families in the Renaissance.

Description

Data frame with the marriage and business links.

Usage

data("links")

Format

A data frame with 36 links (rows) amongst 16 Italian families in the Renaissance.

Albizzi

Acciaiuoli

Barbadori

Bischeri

Castellani

Guadagni

Lamberteschi

Medici

Pazzi

Peruzzi

Ridolfi

Salviati

Strozzi

Tornabuoni

Ginori

Pucci

link

Type of link: marriage or business

Source

PADGETT, J. F. Y C. K. ANSELL (1993): "Robust Action and the Rise of the Medici, 1400-1434", in American Journal of Sociology, 98, 1259-1319. (http://www.jstor.org/stable/2781822)

Examples

data("links")
head(links)

Networked log-linear models.

Description

logCoin produces a network object from loglinear models parameters.

Usage

logCoin(data, variables=names(data), exogenous=NULL, noFirstCat= NULL,
        weight=NULL, order= 2, pairwise=FALSE, twotails = FALSE,
        pmax = 0.05, frequency = FALSE, percentage = FALSE, 
        directed=FALSE, igraph=FALSE, ...)

Arguments

Value

This function creates a netCoin object (or igraph) and, if stated, a folder in the computer with an HTML document named index.html which contains the produced graph. This file can be directly opened with your browser and sent to a web server to work properly.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

References

Escobar, M. and Martinez-Uribe, L. (2020) Network Coincidence Analysis: The netCoin R Package. Journal of Statistical Software, 93, 1-32. doi:10.18637/jss.v093.i11.

Examples

# A n=1,000 sample from the European Social Survey.(Round 8, 2016)
data("ess")
logCoin(ess, c("Social participation", "Political participation"), 
  noFirstCat=c("Social participation", "Political participation"),  
  exogenous=c("Age", "Gender"),  weight = "cweight", 
  order=3, pmax=.05,percentage = TRUE, frequency = TRUE ) # network object

Similarity/distance matrix display.

Description

Display the lower part of a matrix with a specified number of decimals.

Usage

lower(matrix, decimals = 3)

Arguments

Value

A data frame of characters.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

# From a random incidence matrix I(25X4)
I <- matrix(rbinom(100, 1, .5), nrow = 25, ncol = 4,
     dimnames = list(NULL, c("A", "B", "C", "D")))
lower(sim(I, "Jaccard"), 2)

Create a vignette (for galleries).

Description

Create a vignette from w_EntityInfo from wikiTools package (for galleries).

Usage

makeT(data, imageDir=NULL, imageDefault=NULL, language=c("en","es","ca"))

Arguments

Value

a data frame wich includes a column of html formatted vignettes called 'info'.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Create a vignette (for galleries).

Description

Create a vignette from some specific information supplied (for galleries).

Usage

makeT2(entityLabel, image=NA, entityDescription=NA,
    byear=NA, bplace=NA, bcountry=NA, dyear=NA, dplace=NA, dcountry=NA,
    gender=NA, occupation=NA, language=c("en","es","ca"))

Arguments

Value

a data frame wich includes a column of html formatted vignettes called 'info'.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Mobile Edges.

Description

Convert a data frame with one number (normally a year) into an edge list form with those whose numbers (years) have a difference lower or equal to a quantity.

Usage

mobileEdges(data, name = 1, number = 2, difference=0)

Arguments

Value

A data frame in which the two first columns are source and target. The rest of the columns are sim.=(1+threshold-real difference) and dist.=(difference between numbers)

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

# From a random incidence matrix I(25X4)
data("sociologists")
mobileEdges(sociologists)

Produces a gallery of 'netCoin' graphs.

Description

multiPages produces a gallery page to explore multiple 'netCoin' graphs.

Usage

multiPages(x, title = NULL, columns = NULL, imageSize = NULL,
  description = NULL, note = NULL,
  cex = 1, dir = tempDir(), show = FALSE)

Arguments

Value

The function creates a folder in your computer with an HTML document named index.html which contains the graph. This file can be directly opened with your browser.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca.

Examples

# A character column (with separator)
frame <- data.frame(A = c("Man; Women", "Women; Women",
                        "Man; Man", "Undet.; Women; Man"))
data <- dichotomize(frame, "A", sep = "; ")[2:4]
C <- coin(data) # coincidence matrix
N <- asNodes(C) # node data frame
E <- edgeList(C,c("frequency","expected","haberman")) # edge data frame
bC<- barCoin(data,dichotomies="_all") # barCoin object
cC<- barCoin(data,dichotomies="_all",expected=TRUE) # barCoin object
nC<- netCoin(N,E) # netCoin object
multi <- multigraphCreate("Bar graph" = bC,
                  "Conditional bar graph" = cC, 
                  "Net graph"=nC)
## Not run: 
multiPages(multi,"Some graphs",show=TRUE)

## End(Not run)

Produce interactive multi graphs.

Description

multigraphCreate produce an interactive multi graph.

Usage

multigraphCreate(..., mode = c("default","parallel","frame"),
  mfrow = c(1,2),
  frame = 0, speed = 50, loop = FALSE, lineplots = NULL,
  dir = NULL, show = FALSE)

Arguments

Value

This function returns a mGraph object. The function creates a folder in your computer with an HTML document named index.html which contains the graph. This file can be directly opened with your browser.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

# A character column (with separator)
frame <- data.frame(A = c("Man; Women", "Women; Women",
                        "Man; Man", "Undet.; Women; Man"))
data <- dichotomize(frame, "A", sep = "; ")[2:4]
C <- coin(data) # coincidence matrix
N <- asNodes(C) # node data frame
E <- edgeList(C,c("frequency","expected","haberman")) # edge data frame
bC<- barCoin(data,dichotomies="_all") # barCoin object
cC<- barCoin(data,dichotomies="_all",expected=TRUE) # barCoin object
nC<- netCoin(N,E) # netCoin object
multi <- multigraphCreate("Bar graph" = bC,
                  "Conditional bar graph" = cC, 
                  "Net graph"=nC)
## Not run: 
plot(multi)

## End(Not run)

Networked coincidences.

Description

netCoin produces a netCoin object of coincidences. Its input has to be two data.frames: one of attributes of events or nodes, and the other of attributes of the edges or links.

Usage

netCoin(nodes = NULL, links = NULL, tree = NULL,
        community = NULL, layout = NULL,
        name = NULL, label = NULL, group = NULL, groupText = FALSE,
        labelSize = NULL, size = NULL, color = NULL, shape = NULL,
        border = NULL, legend = NULL, sort = NULL, decreasing = FALSE,
        ntext = NULL, info = NULL, image = NULL, imageNames = NULL,
        centrality = NULL,
        nodeBipolar = FALSE, nodeFilter = NULL, degreeFilter = NULL,
        lwidth = NULL, lweight = NULL, lcolor = NULL, ltext = NULL,
        intensity = NULL, linkBipolar = FALSE, linkFilter = NULL,
        repulsion = 25, distance = 10, zoom = 1,
        fixed = showCoordinates, limits = NULL,
        main = NULL, note = NULL, showCoordinates = FALSE, showArrows = FALSE,
        showLegend = TRUE, frequencies = FALSE, showAxes = FALSE,
        axesLabels = NULL, scenarios = NULL, help = NULL, helpOn = FALSE,
        mode = c("network","heatmap"), roundedItems = FALSE, controls = 1:8,
        cex = 1, background = NULL, defaultColor = "#1f77b4",
        language = c("en","es","ca"), dir = NULL)

Arguments

Value

This function returns a netCoin object. If the 'dir' attribute is specified, the function creates a folder in the computer with an HTML document named index.html which contains the produced graph. This file can be directly opened with your browser and sent to a web server to work properly.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

References

Escobar, M. and Martinez-Uribe, L. (2020) Network Coincidence Analysis: The netCoin R Package. Journal of Statistical Software, 93, 1-32. doi:10.18637/jss.v093.i11.

Examples

# A character column (with separator)
frame <- data.frame(A = c("Man; Women", "Women; Women",
                        "Man; Man", "Undet.; Women; Man"))
data <- dichotomize(frame, "A", sep = "; ")[2:4]
C <- coin(data) # coincidence matrix
N <- asNodes(C) # node data frame
E <- edgeList(C) # edge data frame
netCoin(N, E) # netCoin object

Networked correlations.

Description

netCorr produces a network object of correlations. Its input has to be at least one set of quantitative variables.

Usage

netCorr(variables, weight=NULL, pairwise=FALSE,
        minimum=-Inf, maximum=Inf, sort=FALSE, decreasing=TRUE,
        frequency=FALSE, means=TRUE, 
        method=c("pearson", "kendall", "spearman"), 
        criteria="p", Bonferroni=FALSE, minL=0, maxL=Inf,
        sortL=NULL, decreasingL=TRUE,
        igraph=FALSE, ...)

Arguments

Value

The function creates a netCoin object and eventually a folder in the computer with an HTML document named index.html which contains the produced graph. This file can be directly opened with your browser and sent to a web server to work properly.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

# A character column (with separator)
data(iris)
netCorr(iris[,1:4],ltext="value",
 main="Correlations between measurements of Iris Species",
 note="Anderson, Edgar (1935) y Fisher, R. A. (1936)") # network object

Images in a grid gallery.

Description

netExhibit produces an interactive image gallery (alternative display).

Usage

netExhibit(tree, initialType = NULL, tableformat = FALSE, ...)

Arguments

Value

Object of class treeGallery_rd3.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca.

Examples

# Create some film data
tree <- data.frame(
  film = c("The Shawshank Redemption", "The Godfather", "The Dark Knight", "The Godfather Part II",
    "12 Angry Men", "Schindler's List", "The Lord of the Rings: The Return of the King",
    "Pulp Fiction", "The Lord of the Rings: The Fellowship of the Ring",
    "The Good, the Bad and the Ugly"),
  director = c("Frank Darabont", "Francis Ford Coppola", "Christopher Nolan",
    "Francis Ford Coppola", "Sidney Lumet", "Steven Spielberg", "Peter Jackson",
    "Quentin Tarantino", "Peter Jackson", "Sergio Leone"),
  actor = c("Tim Robbins|Morgan Freeman|Bob Gunton", "Marlon Brando|Al Pacino|James Caan",
    "Christian Bale|Heath Ledger|Aaron Eckhart", "Al Pacino|Robert De Niro|Robert Duvall",
    "Henry Fonda|Lee J. Cobb|Martin Balsam", "Liam Neeson|Ralph Fiennes|Ben Kingsley",
    "Elijah Wood|Viggo Mortensen|Ian McKellen", "John Travolta|Uma Thurman|Samuel L. Jackson",
    "Elijah Wood|Viggo Mortensen|Ian McKellen", "Clint Eastwood|Eli Wallach|Lee Van Cleef")
)

gallery <- netExhibit(tree, initialType="film", tableformat=TRUE)

## Not run: 
plot(gallery)

## End(Not run)

Images in a grid gallery.

Description

netGallery produces an interactive image gallery.

Usage

netGallery(tree, deep = FALSE, initialType = NULL, tableformat = FALSE, ...)

Arguments

Value

Object of class netGallery.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca.

Examples

# simply linked tree
tree <- data.frame(
  parent=c("a","a","b","b","b","ab","ab","ab","ab","ba","ba","baa","ba"),
  child=c("aa","ab","ba","bb","bc","aba","abb","abc","abd","baa","bab","baaa","aba")
)

gallery <- netGallery(tree)

## Not run: 
plot(gallery)

## End(Not run)

# Create some film data
tree <- data.frame(
  film = c("The Shawshank Redemption", "The Godfather", "The Dark Knight", "The Godfather Part II",
    "12 Angry Men", "Schindler's List", "The Lord of the Rings: The Return of the King",
    "Pulp Fiction", "The Lord of the Rings: The Fellowship of the Ring",
    "The Good, the Bad and the Ugly"),
  director = c("Frank Darabont", "Francis Ford Coppola", "Christopher Nolan",
    "Francis Ford Coppola", "Sidney Lumet", "Steven Spielberg", "Peter Jackson",
    "Quentin Tarantino", "Peter Jackson", "Sergio Leone"),
  actor = c("Tim Robbins|Morgan Freeman|Bob Gunton", "Marlon Brando|Al Pacino|James Caan",
    "Christian Bale|Heath Ledger|Aaron Eckhart", "Al Pacino|Robert De Niro|Robert Duvall",
    "Henry Fonda|Lee J. Cobb|Martin Balsam", "Liam Neeson|Ralph Fiennes|Ben Kingsley",
    "Elijah Wood|Viggo Mortensen|Ian McKellen", "John Travolta|Uma Thurman|Samuel L. Jackson",
    "Elijah Wood|Viggo Mortensen|Ian McKellen", "Clint Eastwood|Eli Wallach|Lee Van Cleef")
)

gallery <- netGallery(tree, initialType="film", tableformat=TRUE, color="type", zoom=2)

## Not run: 
plot(gallery)

## End(Not run)

# example with path preservation
tree <- rbind(
c("a1","b1","c1|c2"),
c("a2","b2","c3|c4"),
c("a3","b2","c4|c5"),
c("a4","b3|b4","c6|c7|c8")
)

colnames(tree) <- c("a","b","c")

gallery<-netGallery(tree,deep=TRUE,color="type")
## Not run: 
plot(gallery)

## End(Not run)

Structural Equation Models Graphs.

Description

pathCoin produces a netCoin object from a lavaan object, i.e., parameters of structural equation model.

Usage

pathCoin(model, estimates=c("b","se","z","pvalue","beta"), 
         fitMeasures=c("chisq", "cfi", "rmsea"), ...)

Arguments

Value

The function creates a netCoin object and eventually a folder in the computer with an HTML document named index.html which contains the produced graph. This file can be directly opened with your browser and sent to a web server to work properly.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

# Classic Wheaton et al. model
library(lavaan)
lower <- '
11.834
6.947 9.364
6.819 5.091 12.532
4.783 5.028 7.495 9.986
-3.839 -3.889 -3.841 -3.625 9.610
-21.899 -18.831 -21.748 -18.775 35.522 450.288 '
wheaton.cov <- getCov(lower, 
               names = c("anomia67", "powerless67","anomia71", "powerless71",
                         "education", "sei"))
wheaton.model <- '
# latent variables
ses =~ education + sei
alien67 =~ anomia67 + powerless67
alien71 =~ anomia71 + powerless71
# regressions
alien71 ~ alien67 + ses
alien67 ~ ses
# correlated residuals
anomia67 ~~ anomia71
powerless67 ~~ powerless71
'
fit <- sem(wheaton.model, sample.cov = wheaton.cov, sample.nobs = 932)

pathCoin(fit)

pie charts.

Description

It generates pie charts from a coin object.

Usage

pieCoin(x, colors = c("#000000","#8dc7e6", "#ffffff","#005587"),
  nodes = NULL, links = NULL, name = NULL, lcolor = NULL, expected = TRUE,
  abline = NULL, main = NULL, note = NULL, showLegend = TRUE, help = NULL,
  helpOn = FALSE, cex = 1, language = c("en", "es", "ca"), dir = NULL)

Arguments

Value

a pieCoin object.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

## Hair by Eye by Sex table from M. Friendly (2000)
data(HairEyeColor)
H<-as.data.frame(HairEyeColor)
W<-H$Freq
I<-dichotomize(H,c("Hair","Eye","Sex"),add=FALSE)
C <- coin(I,w=W)
pie <- pieCoin(C)
## Not run: 
plot(pie)

## End(Not run)

Express Coin Entries as Fraction of Marginal Table

Description

This is like 'prop.table' for 'coin' objects.

Usage

propCoin(x, margin= 0, decimals=1)

Arguments

Value

Table like 'x' expressed relative to 'margin'.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

## Random incidence matrix: 25 scenarios, 4 events.
I <- matrix(rbinom(100, 1, .5), nrow = 25, ncol = 4,
            dimnames = list(NULL, c("A", "B", "C", "D")))
C <- coin(I, sort = TRUE)

propCoin(C, 1)

Create an html list of links.

Description

Create an html list of links.

Usage

renderLinks(data, columns, labels = NULL, target = "_blank", sites = NULL)

Arguments

Value

a character vector of html formatted links.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

links <- data.frame(name = c(
    "Camarhynchus psitticula",
    "Camarhynchus pauper",
    "Camarhynchus parvulus"
  ), wikipedia=c(
    "https://en.wikipedia.org/wiki/Large_tree_finch",
    "https://en.wikipedia.org/wiki/Medium_tree_finch",
    "https://en.wikipedia.org/wiki/Small_tree_finch"
  ),wikidata=c(
    "https://www.wikidata.org/wiki/Q578835",
    "https://www.wikidata.org/wiki/Q1125857",
    "https://www.wikidata.org/wiki/Q1086136"
  ))
html <- renderLinks(links,c("wikipedia","wikidata"))

Save a netCoin object as a .graphml file to be read in Gephi, Pajek, ...

Description

saveGhml produces a .graphml file from a netCoin object.

Usage

saveGhml(net, file="netCoin.graphml")

Arguments

Value

The function creates a file with vertices and arcs or edges of a netCoin object.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

## Not run: 
# A character column (with separator)
frame <- data.frame(A = c("Man; Women", "Women; Women",
                        "Man; Man", "Undet.; Women; Man"))
data <- dichotomize(frame, "A", add=FALSE, sep = "; ")
graph <- allNet(data, maxL=.5) # graph from an incidence matrix

saveGhml(graph,"graph") # save graph.net file

## End(Not run)

Save a netCoin object as a .net (.paj) file to be read in Pajek, Gephi, ...

Description

savePajek produces a .net (.paj) file from a netCoin object.

Usage

savePajek(net, file="file.net", arcs=NULL, edges=NULL, 
          partitions=NULL, vectors=NULL)

Arguments

Value

The function creates a file with vertices and arcs or edges of a netCoin objetct. Vectors and partitions can be also included. .

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

## Not run: 
# A character column (with separator)
frame <- data.frame(A = c("Man; Women", "Women; Women",
                        "Man; Man", "Undet.; Women; Man"))
data <- dichotomize(frame, "A", add=FALSE, sep = "; ")
graph <- allNet(data) # graph from an incidence matrix

savePajek(graph,"graph",edges="Haberman") # save graph.net file

## End(Not run)

Include netCoin Plots in Shiny.

Description

Load a netCoin plot to display in shiny.

Usage

shinyCoin(x)

Arguments

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

## Not run: 
# A character column (with separator)
frame <- data.frame(A = c("Man; Women", "Women; Women",
                        "Man; Man", "Undet.; Women; Man"))
data <- dichotomize(frame, "A", sep="; ")[2:4]
C <- coin(data) # coincidence matrix
N <- asNodes(C) # node data frame
E <- edgeList(C) # edge data frame
net <- netCoin(N, E) # netCoin object
shinyCoin(net)

## End(Not run)

Similarity matrix.

Description

It calculates a similarity/distance matrix from either an incidence data frame/matrix or a coin object.

Usage

sim(input, procedures="Jaccard", level=.95, distance=FALSE, 
    minimum=1, maximum=Inf, sort=FALSE, decreasing=FALSE, 
    weight = NULL, pairwise = FALSE)

Arguments

Details

Possible measures in procedures are

• Frequencies (f), Relative frequencies (x), Conditional frequencies (i), Coincidence degree (cc), Probable degree (cp),

• Expected (e), Confidence interval (con)

• Matching (m), Rogers & Tanimoto (t), Gower (g), Sneath (s), Anderberg (and),

• Jaccard (j), Dice (d), antiDice (a), Ochiai (o), Kulczynski (k),

• Hamann (ham), Yule (y), Pearson (p), odds ratio (od), Rusell (r),

• Haberman (h), Z value of Haberman (z).

• Hypergeometric p greater value (hyp).

Value

A similarity/distance matrix.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

# From a random incidence matrix I(25X4)
I<-matrix(rbinom(100,1,.5),nrow=25,ncol=4,
   dimnames=list(NULL,c("A","B","C","D")))
sim(I)
#Same results
C<-coin(I)
sim(C)

Data: Classical sociologists.

Description

Data frame with names, birth and death year data, birth country and movement.

Usage

data("sociologists")

Format

A data frame with life's period of 16 sociologists and the following 11 variables to study time coincidences:

name

: name and last name of the sociologist.

birth

: birth year.

death

: death year.

birth_place

: birth place.

birth_country

: birth country.

death_place

: death place.

death_country

: death country.

label

: combination of name, birth and death dates.

generation

: generation (every 25 years) of the sociologists.

school

: school of thought.

picture

: name of the file where their picture is.

Source

Own elaboration from manuals of sociology.

References

See events.

Examples

data(sociologists)
head(sociologists, 10)
tail(sociologists, 10)

Networked coincidences from a data frame.

Description

surCoin produces a network object of coincidences from a data frame converting variables into dichotomies.

Usage

surCoin(data,variables=names(data), commonlabel=NULL,
        dichotomies=NULL, valueDicho=1, metric=NULL, exogenous=NULL,
        weight=NULL, subsample=FALSE, pairwise=FALSE,
        minimum=1, maximum=nrow(data), sort=FALSE, decreasing=TRUE,
        frequency=FALSE, percentages=TRUE,
        procedures="Haberman", criteria="Z", Bonferroni=FALSE,
        support=-Inf, minL=-Inf, maxL=Inf,
        directed=FALSE, diagonal=FALSE, sortL=NULL, decreasingL=TRUE,
        igraph=FALSE, coin=FALSE, dir=NULL, ...)

Arguments

Details

Possible measures in procedures are

• Frequencies (f), Relative frequencies (x), Conditional frequencies (i), Coincidence degree (cc), Probable degree (cp),

• Expected (e), Confidence interval (con)

• Matching (m), Rogers & Tanimoto (t), Gower (g), Sneath (s), Anderberg (and),

• Jaccard (j), Dice (d), antiDice (a), Ochiai (o), Kulczynski (k),

• Hamann (ham), Yule (y), Pearson (p), odds ratio (od), Rusell (r),

• Haberman (h), Z value of Haberman (z),

• Hypergeometric p greater value (hyp).

• Convert a matrix into an edge list (shape).

Value

This function creates a netCoin object (or igraph) and, if stated, a folder in the computer with an HTML document named index.html which contains the produced graph. This file can be directly opened with your browser and sent to a web server to work properly.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

References

Escobar, M. and Martinez-Uribe, L. (2020) Network Coincidence Analysis: The netCoin R Package. Journal of Statistical Software, 93, 1-32. doi:10.18637/jss.v093.i11.

Examples

# A data frame with two variables Gender and Opinion
frame <- data.frame(Gender=c(rep("Man",3),rep("Woman",3)),
                    Opinion=c("Yes","Yes","No","No","No","Yes"))
surCoin(frame,commonlabel="") # network object

# A data frame with two variables (Gender and Hand) and nodes
input <- data.frame(
  Gender = c("Women", "Men", "Men", "Women", "Women","Men",
             "Men", "Men", "Women", "Women", "Men", "Women"),
  Hand   = c("Right", "Left","Right", "Right", "Right", "Right",
             "Left", "Right", "Right", "Left","Right", "Right"))
nodes <- data.frame(
  name  = c("Gender:Men","Gender:Women", "Hand:Left", "Hand:Right"),
  label = c("Women(50\u25)","Men(50\u25)",
            "Left hand(25\u25)", "Right hand(75\u25)"))
G <- surCoin(input, nodes=nodes, proc=c("h","i"), label="label",
             ltext="i", showArrows=TRUE, maxL=.99)

Networked coincidences from a data frame.

Description

surScat produces a network object of coincidences from a data frame converting variables into dichotomies.

Usage

surScat(data, variables=names(data), active=variables, type=c("mca", "pca"), nclusters=2,
        maxN=2000, ...)

Arguments

Details

Possible measures in procedures are

• Frequencies (f), Relative frequencies (x), Conditional frequencies (i), Coincidence degree (cc), Probable degree (cp),

• Expected (e), Confidence interval (con)

• Matching (m), Rogers & Tanimoto (t), Gower (g), Sneath (s), Anderberg (and),

• Jaccard (j), Dice (d), antiDice (a), Ochiai (o), Kulczynski (k),

• Hamann (ham), Yule (y), Pearson (p), odds ratio (od), Rusell (r),

• Haberman (h), Z value of Haberman (z),

• Hypergeometric p greater value (hyp).

• Convert a matrix into an edge list (shape).

Value

This function creates a netCoin object (or igraph) and, if stated, a folder in the computer with an HTML document named index.html which contains the produced graph. This file can be directly opened with your browser and sent to a web server to work properly.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

References

Escobar, M. and Martinez-Uribe, L. (2020) Network Coincidence Analysis: The netCoin R Package. Journal of Statistical Software, 93, 1-32. doi:10.18637/jss.v093.i11.

Examples

# A data frame with two variables Gender and Opinion
frame<-data.frame(Gender=c(rep("Man",3),rep("Woman",3)),
                  Opinion=c("Yes","Yes","No","No","No","Yes"))
surScat(frame) # network object

Networked coincidences.

Description

timeCoin produces a timeCoin object.

Usage

timeCoin(periods, name = "name", start = "start", end = "end", group = NULL,
         text = NULL, main = NULL, note = NULL, info = NULL, 
         events = NULL, eventNames = "name", eventPeriod = "period",
         eventTime = "date", eventColor = NULL, eventShape = NULL,
         cex = 1, language = c("en","es","ca"), dir = NULL)

Arguments

Value

Object of class timeCoin.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

# Database of the classical sociologists.
# Only periods
data(sociologists)
timeCoin(sociologists, "name", "birth", "death", "school")

# Periods and events
data(works)
timeCoin(sociologists, "name", "birth", "death", "school",
         events=works, eventNames="label", eventPeriod="author", eventTime="date")

igraph object.

Description

igraph object from a netCoin object.

Usage

toIgraph(net)

Arguments

Value

An igraph object.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Examples

# A character column (with separator)
frame <- data.frame(A = c("Man; Women", "Women; Women",
                        "Man; Man", "Undet.; Women; Man"))
data <- dichotomize(frame, "A", sep = "; ")[2:4]
C <- coin(data) # coincidence matrix
N <- asNodes(C) # node data frame
E <- edgeList(C)
net <- netCoin(N, E)
toIgraph(net) # conversion into a igraph object

Data: Classical sociological works.

Description

Data frame with classical sociological works writen by authors in the sociologists data frame.

Usage

data("sociologists")

Format

A data frame with 54 observations (events) and the following 4 variables to study coincidences in time:

name

: name and last name of the author of the work.

label

: abbreviation of the complete name.

works

: work's name.

date

: year of its first publication.

Author(s)

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Source

Own elaboration from manuals of sociology.

References

See events.

Examples

data(works)
head(works, 10)
tail(works, 10)