Type: | Package |
Title: | Perform Polynomial Evaluation of Linearity |
Version: | 0.1.2 |
Author: | Vishesh Shrivastav |
Maintainer: | Vishesh Shrivastav <vishesh2k6@gmail.com> |
Description: | Evaluates whether the relationship between two vectors is linear or nonlinear. Performs a test to determine how well a linear model fits the data compared to higher order polynomial models. Jhang et al. (2004) <doi:10.1043/1543-2165(2004)128%3C44:EOLITC%3E2.0.CO;2>. |
Imports: | broom |
License: | MIT + file LICENSE |
Encoding: | UTF-8 |
LazyData: | true |
RoxygenNote: | 6.1.1 |
Suggests: | knitr |
VignetteBuilder: | knitr |
NeedsCompilation: | no |
Packaged: | 2019-02-21 21:28:33 UTC; Shrivatav |
Repository: | CRAN |
Date/Publication: | 2019-02-22 00:00:03 UTC |
Computes average deviation from linearity adl.
Description
Computes average deviation from linearity adl.
Usage
calculate_adl(predicted.poly, predicted.lm)
Arguments
predicted.poly |
vector of predicted values from best-fitting polynomial model |
predicted.lm |
vector of predicted values from linear model |
Value
value for average deviation from linearity as a percentage
Establishes if relationship between two vectors is linear or nonlinear. Does not return any value. Prints details of the relationship between x and y.
Description
Establishes if relationship between two vectors is linear or nonlinear. Does not return any value. Prints details of the relationship between x and y.
Usage
poly_eval(y, x, threshold)
Arguments
y |
vector of response values |
x |
vector of predictor values |
threshold |
optional argument. Threshold percentage value for average deviation from linearity. Defaults to 5. |
Examples
foo <- c(1000, 4000, 5000, 4500, 3000, 4000, 9000, 11000, 15000, 12000, 7000, 3000)
bar <- c(9914, 40487, 54324, 50044, 34719, 42551, 94871, 118914, 158484, 131348, 78504, 36284)
poly_eval(bar, foo)