Single- And Multiple-Group Penalized Factor Analysis
c(person(given = "Elena",
family = "Geminiani",
role = c("aut", "cre"),
email = "geminianielena@gmail.com",
comment = c(ORCID = "0000-0001-5992-9728")),
person(given = "Giampiero",
family = "Marra",
role = c("aut"),
email = "giampiero.marra@ucl.ac.uk",
comment = c(ORCID = "0000-0002-9010-2646")),
person(given = "Irini",
family = "Moustaki",
role = c("aut"),
email = "i.moustaki@lse.ac.uk",
comment = c(ORCID = "0000-0001-8371-1251"))
)
Fits single- and multiple-group penalized factor analysis models
via a trust-region algorithm with integrated automatic multiple tuning
parameter selection (Geminiani et al., 2021 <doi:10.1007/s11336-021-09751-8>).
Available penalties include lasso, adaptive lasso, scad, mcp, and ridge.
MASS, methods, mgcv, GJRM, stats, trust, utils

Penalized Poisson Pseudo Maximum Likelihood Regression
c(
person(given = "Diego",
family = "Ferreras Garrucho",
role = "aut",
email = "d.ferreras-garrucho@lse.ac.uk"),
person(given = "Tom",
family = "Zylkin",
role = "aut",
email = "tzylkin@richmond.edu"),
person(given = "Nicolas",
family = "Apfel",
role = "cre",
email = "nicolas.apfel@gmail.com")
)
A set of tools that enables efficient estimation of penalized
Poisson Pseudo Maximum Likelihood regressions, using lasso or ridge penalties, for models
that feature one or more sets of high-dimensional fixed effects. The methodology is based on
Breinlich, Corradi, Rocha, Ruta, Santos Silva, and Zylkin (2021) <http://hdl.handle.net/10986/35451>
and takes advantage of the method of alternating projections of Gaure (2013)
<doi:10.1016/j.csda.2013.03.024> for dealing with HDFE, as well as
the coordinate descent algorithm of Friedman, Hastie and Tibshirani (2010)
<doi:10.18637/jss.v033.i01> for fitting lasso regressions. The package is also able to carry out
cross-validation and to implement the plugin lasso of Belloni, Chernozhukov, Hansen and Kozbur (2016)
<doi:10.1080/07350015.2015.1102733>.
Rcpp, glmnet, lfe, ncvreg, tidyr, rlang, magrittr
testthat (>= 3.0.0), MASS, knitr, rmarkdown, directlabels,
ggplot2, reshape2
Diego Ferreras Garrucho [aut],
Tom Zylkin [aut],
Nicolas Apfel [cre]