projpred/DESCRIPTION at master · stan-dev/projpred · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
Package: projpred
Encoding: UTF-8
Title: Projection Predictive Feature Selection
Version: 2.10.0.9000
Date: 2025-12-05
Authors@R: c(person("Juho", "Piironen", role = c("aut"),
                    email = "juho.t.piironen@gmail.com"),
             person("Markus", "Paasiniemi", role = "aut"),
             person("Alejandro", "Catalina", role = "aut",
                    email = "alecatfel@gmail.com"),
             person("Frank", "Weber", role = "aut"),
             person("Osvaldo", "Martin", role = c("cre", "aut"),
                    email = "aloctavodia@gmail.com"),
             person("Aki", "Vehtari", role = "aut"),
             person("Jonah", "Gabry", role = "ctb"),
             person("Marco", "Colombo", role = "ctb"),
             person("Paul-Christian", "Bürkner", role = "ctb"),
             person("Hamada S.", "Badr", role = "ctb"),
             person("Brian", "Sullivan", role = "ctb"),
             person("Sölvi", "Rögnvaldsson", role = "ctb"),
             person(family = "The LME4 Authors", role = "cph",
                    comment = "see file 'LICENSE' for details"),
             person("Yann", "McLatchie", role = "ctb"),
             person("Juho", "Timonen", role = "ctb"))
Description:
    Performs projection predictive feature selection for generalized linear
    models (Piironen, Paasiniemi, and Vehtari, 2020, <doi:10.1214/20-EJS1711>)
    with or without multilevel or additive terms (Catalina, Bürkner, and
    Vehtari, 2022, <https://proceedings.mlr.press/v151/catalina22a.html>), for
    some ordinal and nominal regression models (Weber, Glass, and Vehtari, 2025,
    <doi:10.1007/s00180-024-01506-0>), and for many other regression models
    (using the latent projection by Catalina, Bürkner, and Vehtari, 2021,
    <doi:10.48550/arXiv.2109.04702>, which can also be applied to most of the
    former models). The package is compatible with the 'rstanarm' and 'brms'
    packages, but other reference models can also be used. See the vignettes and
    the documentation for more information and examples.
License: GPL-3 | file LICENSE
URL: https://mc-stan.org/projpred/, https://discourse.mc-stan.org
BugReports: https://github.com/stan-dev/projpred/issues/
Depends:
    R (>= 3.6.0)
Imports:
    methods,
    utils,
    Rcpp,
    gtools,
    ggplot2,
    scales,
    rstantools (>= 2.0.0),
    loo (>= 2.0.0),
    lme4 (>= 1.1-28),
    mvtnorm,
    mgcv,
    gamm4,
    abind,
    MASS,
    ordinal,
    nnet,
    mclogit,
    reformulas,
Suggests:
    ggrepel,
    ggfortify,
    rstanarm,
    brms,
    nlme,
    optimx,
    ucminf,
    parallel,
    foreach,
    iterators,
    doRNG,
    unix,
    testthat,
    vdiffr,
    knitr,
    rmarkdown,
    glmnet,
    cmdstanr,
    rlang,
    bayesplot (>= 1.5.0),
    posterior,
    doParallel,
    future,
    future.callr,
    doFuture,
    progressr
LinkingTo: Rcpp, RcppArmadillo
Additional_repositories:
    https://stan-dev.r-universe.dev/
LazyData: TRUE
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.3
VignetteBuilder: knitr, rmarkdown