我想知道是否有人会知道一个r套件，它可以让我与套索正则化合适的序数逻辑回归，还是在套索中仍然是beta回归？而且，如果您还知道一个很好的教程可以帮助我编码R（具有适当的交叉验证），那会更好！
某些上下文：我的响应变量是0到10之间的满意度得分（实际上，值在2到10之间），因此我可以用beta回归对其进行建模，否则我可以将其值转换为排名类别。我的兴趣是识别重要变量解释 与我的样本量相比，我有太多潜在的解释变量（ p = 12）（ p = 12） （ n = 105），我需要使用惩罚回归方法进行模型选择，因此我对套索的兴趣。
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? 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!
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. 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.
发布评论
评论（1）
ordinalnet软件包执行此操作。这里有一篇论文，例如：https://wwwww.statsoft.org/article.org/article/article/article/download/download/download/download/download/v099i06/144444440
另外
glmnetcr软件包：The
ordinalNetpackage does this. There's a paper with example here:https://www.jstatsoft.org/article/download/v099i06/1440
Also the
glmnetcrpackage: https://cran.r-project.org/web/packages/glmnetcr/vignettes/glmnetcr.pdf