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LogisticCopula
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Download and install LogisticCopula package within the R console
Install from CRAN:
install.packages("LogisticCopula")
Install from Github:
library("remotes")
install_github("cran/LogisticCopula")
Install by package version:
library("remotes")
install_version("LogisticCopula", "0.1.0")
Attach the package and use:
library("LogisticCopula")
Maintained by
Simon Boge Brant
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.LogisticCopula . LogisticCopula results . LogisticCopula.pdf . LogisticCopula_0.1.0.tar.gz . LogisticCopula_0.1.0.zip . LogisticCopula_0.1.0.zip . LogisticCopula_0.1.0.zip . LogisticCopula_0.1.0.tgz . LogisticCopula_0.1.0.tgz . LogisticCopula_0.1.0.tgz . LogisticCopula_0.1.0.tgz . LogisticCopula_0.1.0.tgz . LogisticCopula_0.1.0.tgz . https://CRAN.R-project.org/package=LogisticCopula .
First Published: 2024-06-28
Latest Update: 2024-06-28
Description:
An implementation of a method of extending a logistic regression model beyond linear effects of the co-variates. The extension in is constructed by first equating the logistic regression model to a naive Bayes model where all the margins are specified to follow natural exponential distributions conditional on Y, that is, a model for Y given X that is specified through the distribution of X given Y, where the columns of X are assumed to be mutually independent conditional on Y. Subsequently, the model is expanded by adding vine - copulas to relax the assumption of mutual independence, where pair-copulas are added in a stage-wise, forward selection manner. Some heuristics are employed during the process of selecting edges, as well as the families of pair-copula models. After each component is added, the parameters are updated by a (smaller) number of gradient steps to maximise the likelihood. When the algorithm has stopped adding edges, based the criterion that a new edge should improve the likelihood more than k times the number new parameters, the parameters are updated with a larger number of gradient steps, or until convergence.
How to cite:
Simon Boge Brant (2024). LogisticCopula: A Copula Based Extension of Logistic Regression. R package version 0.1.0, https://cran.r-project.org/web/packages/LogisticCopula. Accessed 21 Feb. 2025.
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