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R中带有LASSO正则化的有序逻辑回归（或Beta回归）？

[英]Ordinal logistic regression (or Beta regression) with a LASSO regularization in R?

原文 2022-06-16 10:44:47 5 1 r/ logistic-regression/ cross-validation/ lasso-regression/ betareg

I was wondering if someone would know an R package that would allow me to fit an Ordinal Logistic regression with a LASSO regularization or, alternatively, a Beta regression still with the LASSO?我想知道是否有人会知道一个 R 包，它允许我使用 LASSO 正则化拟合 Ordinal Logistic 回归，或者仍然使用 LASSO 进行 Beta 回归？ And if you also know of a nice tutorial to help me code that in R (with appropriate cross-validation), that would be even better!如果您还知道一个很好的教程来帮助我在 R 中编写代码（使用适当的交叉验证），那就更好了！

Some context: My response variable is a satisfaction score between 0 and 10 (actually, values lie between 2 and 10) so I can model it with a Beta regression or I can convert its values into ranked categories.一些背景：我的响应变量是 0 到 10 之间的满意度分数（实际上，值介于 2 到 10 之间），因此我可以使用 Beta 回归对其进行建模，或者我可以将其值转换为排名类别。 My interest is to identify important variables explaining this score but as I have too many potential explanatory variables ( p = 12) compared to my sample size ( n = 105), I need to use a penalized regression method for model selection, hence my interest in the LASSO.我的兴趣是确定解释这个分数的重要变量，但由于与我的样本量（ n = 105）相比，我有太多潜在的解释变量（ p = 12），我需要使用惩罚回归方法进行模型选择，因此我的兴趣在套索。

1 个解决方案

The ordinalNet package does this. ordinalNet包就是这样做的。 There's a paper with example here: https://www.jstatsoft.org/article/download/v099i06/1440这里有一篇带示例的论文： https ://www.jstatsoft.org/article/download/v099i06/1440

Also the glmnetcr package: https://cran.r-project.org/web/packages/glmnetcr/vignettes/glmnetcr.pdf还有glmnetcr包： https ://cran.r-project.org/web/packages/glmnetcr/vignettes/glmnetcr.pdf