Suggests: MASS, aod, lme4, pscl, leaps, survival, nnet
wrapper for glm and other functions, automatically generating

Title: Model Selection and Multimodel Inference Made Easy

Package: glmulti
Version: 1.0.8
Date: 2020-05-25
Title: Model Selection and Multimodel Inference Made Easy
Author: Vincent Calcagno [aut, cre]
Maintainer: Vincent Calcagno <vincent.calcagno@inrae.fr>
Authors@R: person("Vincent", "Calcagno", email = "vincent.calcagno@inrae.fr",role = c("aut", "cre"))
SystemRequirements: Java (>= 5.0)
Depends: R (>= 2.13.0), rJava (>= 0.5-0), methods, leaps
Suggests: MASS, aod, lme4, pscl, survival, nnet
Description: Automated model selection and model-averaging. Provides a
wrapper for glm and other functions, automatically generating
all possible models (under constraints set by the user) with
the specified response and explanatory variables, and finding
the best models in terms of some Information Criterion (AIC,
AICc or BIC). Can handle very large numbers of candidate
models. Features a Genetic Algorithm to find the best models
when an exhaustive screening of the candidates is not feasible.
License: GPL (>= 2)
Packaged: 2020-05-26 07:56:26 UTC; cvince
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2020-05-26 11:00:08 UTC

Title: Variable Selection Deviation (VSD) Measures and Instability
Tests for High-dimensional Generalized Linear Models
Author: Ying Nan <nanx0006@gmail.com>, Yi Yang <yiyang@umn.edu>, Yuhong Yang <yyang@stat.umn.edu>
Description: Variable selection deviation measures and instability tests for high-dimensional model selection methods such as LASSO, SCAD and MCP, etc., to decide whether the sparse patterns identified by those methods are reliable.

Title: Variable Selection Deviation Measures and Instability Tests for
Description: Variable selection deviation (VSD) measures and instability tests for high-dimensional model selection methods such as LASSO, SCAD and MCP, etc., to decide whether the sparse patterns identified by those methods are reliable.

Author: Ying Nan <nanx0006@gmail.com>, Yi Yang <yiyang@umn.edu>, Yuhong Yang <yyang@stat.umn.edu>, Chenglong Ye <yexxx323@umn.edu>