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RRMLRfMC
View on CRAN: Click
here
Download and install RRMLRfMC package within the R console
Install from CRAN:
install.packages("RRMLRfMC")
Install from Github:
library("remotes")
install_github("cran/RRMLRfMC")
Install by package version:
library("remotes")
install_version("RRMLRfMC", "0.4.0")
Attach the package and use:
library("RRMLRfMC")
Maintained by
Pei Wang
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-06-07
Latest Update: 2021-06-07
Description:
Fit the reduced-rank multinomial logistic regression model for Markov chains developed by Wang, Abner, Fardo, Schmitt, Jicha, Eldik and Kryscio (2021)<doi:10.1002/sim.8923> in R. It combines the ideas of multinomial logistic regression in Markov chains and reduced-rank. It is very useful in a study where multi-states model is assumed and each transition among the states is controlled by a series of covariates. The key advantage is to reduce the number of parameters to be estimated. The final coefficients for all the covariates and the p-values for the interested covariates will be reported. The p-values for the whole coefficient matrix can be calculated by two bootstrap methods.
How to cite:
Pei Wang (2021). RRMLRfMC: Reduced-Rank Multinomial Logistic Regression for Markov Chains. R package version 0.4.0, https://cran.r-project.org/web/packages/RRMLRfMC
Previous versions and publish date:
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Functions, R codes and Examples using
the RRMLRfMC R package
Some associated functions: Aupdate . Gupdate . cogdat . derivativeB . derivatives . expand . norm . rrmultinom . sdfun .
Some associated R codes: Aupdate.R . Gupdate.R . cogdat.R . derivativeB.R . derivatives.R . expand.R . norm.R . rrmultinom.R . sdfun.R . Full RRMLRfMC package functions and examples
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