| Type: | Package |
| Title: | Stepwise Regression with Assumptions Checking |
| Version: | 0.1.2 |
| Description: | The stepwise regression with assumptions checking and the possible Box-Cox transformation. |
| License: | GPL-3 |
| Encoding: | UTF-8 |
| Imports: | car, dplyr, MASS |
| RoxygenNote: | 7.2.0 |
| Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0) |
| VignetteBuilder: | knitr |
| Config/testthat/edition: | 3 |
| NeedsCompilation: | no |
| Packaged: | 2022-08-10 15:39:22 UTC; PC |
| Author: | Thidarat Thongsri [aut, cre], Klairung Samart [aut] |
| Maintainer: | Thidarat Thongsri <k.th.thidarat@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2022-08-10 16:10:09 UTC |
Perform stepwise regression with verifying assumptions and identifying possible Box-Cox transformation
Description
A tool for multiple regression, select independent variables, check multiple linear regression assumptions and identify possible.
Usage
mlrpro(Data,Y,Column_Y,Alpha)
Arguments
Data |
a data frame containing the variables in the model. |
Y |
the response variable. |
Column_Y |
the column response variable. |
Alpha |
significance level. |
Value
An object of class mlrpro is a list containing at least the following components:
coefficients |
a named vector of coefficients. |
residuals |
the residuals, that is response minus fitted values. |
fitted.values |
the fitted mean values. |
rank |
the numeric rank of the fitted linear model. |
df.residual |
the residual degrees of freedom. |
call |
the matched call. |
terms |
the terms object used. |
model |
if requested (the default), the model frame used. |
lambda |
lambda value utilized in the data conversion. |
Examples
data(trees)
Model1 <- mlrpro(Data = trees,Y = trees$Volume, Column_Y = 3, Alpha = 0.05)
## or ##
data(mtcars)
Model2 <- mlrpro(Data = mtcars,Y = mtcars$mpg, Column_Y = 1 , Alpha = 0.01)