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stepjglm  

Variable Selection for Joint Modeling of Mean and Dispersion
View on CRAN: Click here


Download and install stepjglm package within the R console
Install from CRAN:
install.packages("stepjglm")

Install from Github:
library("remotes")
install_github("cran/stepjglm")

Install by package version:
library("remotes")
install_version("stepjglm", "0.0.1")



Attach the package and use:
library("stepjglm")
Maintained by
Leandro A. Pereira
[Scholar Profile | Author Map]
First Published: 2021-10-25
Latest Update: 2021-10-25
Description:
A Package for selecting variables for the joint modeling of mean and dispersion (including models for mixture experiments) based on hypothesis testing and the quality of model's fit. In each iteration of the selection process, a criterion for checking the goodness of fit is used as a filter for choosing the terms that will be evaluated by a hypothesis test. Pinto & Pereira (2021) <doi:10.48550/arXiv.2109.07978>.
How to cite:
Leandro A. Pereira (2021). stepjglm: Variable Selection for Joint Modeling of Mean and Dispersion. R package version 0.0.1, https://cran.r-project.org/web/packages/stepjglm. Accessed 18 Apr. 2025.
Previous versions and publish date:
No previous versions
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Complete documentation for stepjglm
Functions, R codes and Examples using the stepjglm R package
Some associated functions: bread_mixture . injection_molding . stepjglm . 
Some associated R codes: aux1.R . bread_mixture.R . calcula.rsq.R . calculaqde.R . globals.R . injection_molding.R . stepdisp.R . stepdisp2.R . stepjglm.R . stepmean.R . stepmean2.R .  Full stepjglm package functions and examples
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