Year: 2026
Type: preprint
Abstract: Plausbility is a theoretical framework that allows to conduct exact inference in general parametric families. We introduce R-packages {\em plausibility} that implements this framework for a wide class of regression models. Plausibility can also be used to test penalized regression models such as estimated by package {\em glmnet}. We illustrate the package using a number of R data sets Through a class-based mechanism, the package can be easily extended. We illustrate and discuss computation aspects of the implementation and their impact on real-data analysis.
Source: arXiv (Cornell University)
Authors: Böhringer, Stefan, Swen, Jesse
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7167255304
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