| Type: | Package |
| Title: | Spatial Microsimulation |
| Version: | 2.3.1 |
| Date: | 2015-11-10 |
| Author: | Dimitris Kavroudakis <dimitris123@gmail.com> |
| Maintainer: | Dimitris Kavroudakis <dimitris123@gmail.com> |
| Description: | Produce small area population estimates by fitting census data to survey data. |
| License: | GPL-3 |
| LazyLoad: | yes |
| Depends: | doParallel, foreach, parallel, methods, iterators, stats |
| RoxygenNote: | 5.0.0 |
| NeedsCompilation: | no |
| Packaged: | 2015-11-14 15:10:12 UTC; dimitrisk |
| Repository: | CRAN |
| Date/Publication: | 2015-11-15 10:09:12 |
Spatial Microsimulation Library
Description
Generate small area population microdata from census and survey datasets. Fit the survey data to census area descriptions and export the population of small areas (microdata).
Details
Generate small area population microdata from census and panel datasets. Fit the survey data to census area descriptions and export the popultion of small areas.
Author(s)
Dimitris Kavroudakis dimitris123@gmail.com
References
Dimitris Kavroudakis D (2015). sms: An R Package for the Construction of Microdata for Geographical Analysis. Journal of Statistical Software, 68(2), pp. 1-23. http://10.18637/jss.v068.i02
addDataAssociation
Description
Create a data lexicon for holding the associated column names
Usage
addDataAssociation(indf, data_names)
Arguments
indf |
A data Lexicon (data.frame) created from the function: |
data_names |
A vector vith two elements. The first element should be the name of
the |
Value
indf The imported data lexicon with one extra column.
Author(s)
Dimitris Kavroudakis dimitris123@gmail.com
Examples
library(sms)
data(survey)
data(census)
in.lexicon=createLexicon()
in.lexicon=addDataAssociation(in.lexicon, c("he","he"))
in.lexicon=addDataAssociation(in.lexicon, c("females","female"))
print(in.lexicon)
Calculate error of a selection
Description
Calculate the error of a selection.
Usage
calculate_error(selection, area_census, lexicon)
Arguments
selection |
A population selection, to evaluate its error |
area_census |
An area from census (a row) |
lexicon |
A data.frame with details about data connections |
Details
Calculates the Total Absolute Error (TAE) of a selection for a census area.
Value
TAE Total Absolute Error of this selection against the census description of this area.
Author(s)
Dimitris Kavroudakis dimitris123@gmail.com
Examples
library(sms)
data(survey) #load the data
data(census)
in.lexicon=createLexicon() # Create a data lexicon for holding the associated column names.
in.lexicon=addDataAssociation(in.lexicon, c("he","he"))
in.lexicon=addDataAssociation(in.lexicon, c("females","female"))
#Select the first area from the census table
this_area=as.data.frame(census[1,])
#make a random selection of individuals for this area.
selection=random_panel_selection( survey, this_area$population )
#evaluate the Total Absolute Error (TAE) for this selection
error=calculate_error( selection, this_area, in.lexicon )
print( error ) # print the error of the selection
A census dataset of 10 areas
Description
A sample census dataset containing descriptive information about 10 geographical areas. The variables in the dataset are as follows:
areaid: The unique indentifier of the area
population: The number of indivisuals in the area.
he: Number of individuals in the area, with at least Higher Education degree
females: Number of female individuals in the area
Usage
data(census)
Format
A data frame with 10 rows and 4 variables
checkIfNamesInDataColumns
Description
Check the integrisy of the data Lexicon
Usage
checkIfNamesInDataColumns(names, incensus, insurvey)
Arguments
names |
A vector with names to check if they exist as column names in the data (census and survey) |
incensus |
The census data |
insurvey |
The survey data |
Value
anumber If both names are valid then it return '1' else if the names are not valid data column names, it returns '0'.
Author(s)
Dimitris Kavroudakis dimitris123@gmail.com
check_lexicon
Description
Check the lexicon data.frame
Usage
check_lexicon(inlex)
Arguments
inlex |
A data.frame which will be used a data lexicon for listing the associated data columns. |
Author(s)
Dimitris Kavroudakis dimitris123@gmail.com
Examples
library(sms)
df=createLexicon()
df=addDataAssociation(df, c("ena","duo"))
check_lexicon(df)
createLexicon
Description
Create a data lexicon for holding the associated column names
Usage
createLexicon()
Value
dataLexicon A data.frame holding the associated column names.
Author(s)
Dimitris Kavroudakis dimitris123@gmail.com
Examples
library(sms)
data(survey)
data(census)
in.lexicon=createLexicon()
in.lexicon=addDataAssociation(in.lexicon, c("he","he"))
in.lexicon=addDataAssociation(in.lexicon, c("females","female"))
print(in.lexicon)
find_best_selection
Description
Find the best selection of individual records for a census area.
Usage
find_best_selection(area, insms, inseed = -1)
Arguments
area |
A census area |
insms |
A microsimulation object which holds the data and details of the simulation such as iterations, lexicon. |
inseed |
test |
Details
Calculate the best area representation, after a series of selection tries.
Value
list A list with results (#areaid, #selection, #tae, #tries, #error_states).
Author(s)
Dimitris Kavroudakis dimitris123@gmail.com
Examples
library(sms)
data(survey) #load the data
data(census)
in.lexicon=createLexicon() # Create a data lexicon for holding the associated column names.
in.lexicon=addDataAssociation(in.lexicon, c("he","he"))
in.lexicon=addDataAssociation(in.lexicon, c("females","female"))
this_area=as.data.frame(census[1,]) #Select the first area from the census table
insms= new("microsimulation",census=census,panel=survey, lexicon=in.lexicon, iterations=10)
best=find_best_selection(this_area, insms)
print(best)
find_best_selection_SA
Description
Run a simulation in parallel mode with Simulated Annealing
Usage
find_best_selection_SA(area_census, insms, inseed = -1)
Arguments
area_census |
A census dataset consisting of various areas rows. |
insms |
A microsimulation object which holds the data and details of the simulation such as iterations, lexicon. |
inseed |
A number to be used for random seed. |
Value
msm_results An object with the results of the simulation, of this area.
Author(s)
Dimitris Kavroudakis dimitris123@gmail.com
Examples
library(sms)
data(survey)
data(census)
in.lexicon=createLexicon()
in.lexicon=addDataAssociation(in.lexicon, c("he","he"))
in.lexicon=addDataAssociation(in.lexicon, c("females","female"))
this_area=as.data.frame(census[1,]) #Select the first area from the census table
insms= new("microsimulation",census=census, panel=survey, lexicon=in.lexicon, iterations=5)
myselection= find_best_selection_SA( this_area, insms, inseed=1900)
print(myselection)
getInfo Generic
Description
getInfo Generic
Usage
getInfo(object)
Arguments
object |
A microsimulation object to get its information. |
Author(s)
Dimitris Kavroudakis dimitris123@gmail.com
getInfo Method
Description
Get information from a microsimulation object
Usage
## S4 method for signature 'microsimulation'
getInfo(object)
Arguments
object |
A microsimulation object to get its information. |
Author(s)
Dimitris Kavroudakis dimitris123@gmail.com
getTAEs Generic
Description
Get the TAE from a microsimulation object.
Usage
getTAEs(object)
Arguments
object |
A microsimulation object to get its information. |
Author(s)
Dimitris Kavroudakis dimitris123@gmail.com
getTAEs Method
Description
getTAEs Method
Usage
## S4 method for signature 'microsimulation'
getTAEs(object)
Arguments
object |
A microsimulation object to get its information. |
Value
taes A list of numbers indicating the Total Absolute Error of the fitting process for each of the census areas.
Author(s)
Dimitris Kavroudakis dimitris123@gmail.com
A microsimulation object
Description
It holds all microsimulation details and objects such as data, results etc.
Arguments
census: |
A census data.frame where each row contains census information about a geographical area |
panel: |
A data.frame containing the individual based records from a panel survey. Those data will be fitted to small area contrains and will populate each vrtual area. |
lexicon: |
A data.frame containing the association of columns between census data and panel data. Each row contain a conection between census and panel data.frame. |
resuls: |
A list of results from the fitting process. |
iterations: |
The number of itertions until th end of the fitting process. |
Author(s)
Dimitris Kavroudakis dimitris123@gmail.com
mysetSeed
Description
mysetSeed
Usage
mysetSeed(inseed)
Arguments
inseed |
A number to set as a random seed. |
Details
mysetSeed
Examples
library(sms)
sms::mysetSeed(1900)
Plot selection results
Description
Plot the selection process of an area from a microsimulation object.
Usage
plotTries(insms, number)
Arguments
insms |
The input results |
number |
the number of the area to plot |
Details
Plot errors during selection process for an area.
Author(s)
Dimitris Kavroudakis dimitris123@gmail.com
Examples
library(sms)
data(survey) #load the data
data(census)
in.lexicon=createLexicon() # Create a data lexicon for holding the associated column names.
in.lexicon=addDataAssociation(in.lexicon, c("he","he"))
in.lexicon=addDataAssociation(in.lexicon, c("females","female"))
ansms = new("microsimulation", census=census, panel=survey, lexicon=in.lexicon, iterations=5)
sa = run_parallel_SA(ansms, inseed=1900)
plotTries( sa, 1 )
random_panel_selection
Description
Select n random rows from a dataframe
Usage
random_panel_selection(indf, n)
Arguments
indf |
The initial dataframe from wich a selection will be made. |
n |
The number of random rows |
Details
Select n random rows from a dataframe
Value
a selection of rows as a dataframe
Author(s)
Dimitris Kavroudakis dimitris123@gmail.com
Examples
library(sms)
data(survey) #load the data
data(census)
some.individuals=random_panel_selection(survey,4)
print(some.individuals) # Print the selection of individuals
run_parallel_HC
Description
Run a simulation in serial mode with Hill Climbing
Usage
run_parallel_HC(insms, inseed = -1)
Arguments
insms |
A microsimulation object which holds the data and details of the simulation such as iterations, lexicon. |
inseed |
A number to be used for random seed. |
Details
Run a simulation in serial mode with Hill Climbing
Value
msm_results An object with the results of the simulation, for each area.
Author(s)
Dimitris Kavroudakis dimitris123@gmail.com
Examples
library(sms)
data(survey) #load the data
data(census)
in.lexicon=createLexicon() # Create a data lexicon for holding the associated column names.
in.lexicon=addDataAssociation(in.lexicon, c("he","he"))
in.lexicon=addDataAssociation(in.lexicon, c("females","female"))
insms= new("microsimulation",census=census,panel=survey, lexicon=in.lexicon, iterations=10)
re=run_parallel_HC(insms, inseed=1900)
print(re)
run_parallel_SA
Description
Run a simulation in parallel mode with Simulated Annealing
Usage
run_parallel_SA(insms, inseed = -1)
Arguments
insms |
A microsimulation object which holds the data and details of the simulation such as iterations, lexicon. |
inseed |
A random number to be used for random seed. |
Value
msm_results An object with the results of the simulation, for each area.
Author(s)
Dimitris Kavroudakis dimitris123@gmail.com
Examples
library(sms)
data(survey)
data(census)
in.lexicon=createLexicon()
in.lexicon=addDataAssociation(in.lexicon, c("he","he"))
in.lexicon=addDataAssociation(in.lexicon, c("females","female"))
insms= new("microsimulation",census=census, panel=survey, lexicon=in.lexicon, iterations=5)
results= run_parallel_SA(insms, inseed=1900)
print(results)
Run_serial
Description
Run a simulation in serial mode
Usage
run_serial(insms)
Arguments
insms |
A microsimulation object which holds the data and details of the simulation such as iterations, lexicon. |
Details
Run a simulation in serial mode.
Value
msm_results An object with the results of the simulation, for each area.
Author(s)
Dimitris Kavroudakis dimitris123@gmail.com
Examples
library(sms)
data(survey)
data(census)
in.lexicon=createLexicon()
in.lexicon=addDataAssociation(in.lexicon, c("he","he"))
in.lexicon=addDataAssociation(in.lexicon, c("females","female"))
insms= new("microsimulation",census=census, panel=survey, lexicon=in.lexicon, iterations=5)
results= run_serial( insms)
print(results)
selection_for_area
Description
Make a single selection of individual records for a census area.
Usage
selection_for_area(inpanel, area_census, inlexicon)
Arguments
inpanel |
The panel dataset |
area_census |
A census area |
inlexicon |
A data lexicon showing the variable associations. |
Details
Select a number of individual records from panel dataset, to represent a census description of an area.
Value
list A list of results (#areaid, #selection, #error)
Author(s)
Dimitris Kavroudakis dimitris123@gmail.com
Examples
library(sms)
data(survey) #load the data
data(census)
in.lexicon=createLexicon() # Create a data lexicon for holding the associated column names.
in.lexicon=addDataAssociation(in.lexicon, c("he","he"))
in.lexicon=addDataAssociation(in.lexicon, c("females","female"))
# Select the first area from the census table
this_area=as.data.frame(census[1,])
#make a representation for this area.
sel=selection_for_area(survey, this_area, in.lexicon)
print(sel) #print the representation
A survey dataset of 200 individuals
Description
A sample survey dataset containing binary (0 or 1) information about 200 individuals. Those individuals will be used to populate the simulated areas. The variables in the dataset are as follows:
pid: The unique indentifier of the individual
female: Binary value of the sex of the individual. 1-Female, 0-Male
agemature: Binary value indicating if the individual belongs to the mature age group. 0-No, 1-Yes
car_owner: Binary value indicating if the individual owns a car. 0-No, 1-Yes
house_owner: Binary value indicating if the individual owns a house. 0-No, 1-Yes
working: Binary value indicating if the individual is working. 0-No, 1-Yes
Usage
data(survey)
Format
A data frame with 200 rows and 7 variables