Imports data from the Our World in Data website, offering easy to use functions for searching for datasets, downloading them into R and visualising them.
testthat (>= 3.0.0), utils, showtext, sysfonts, knitr,
rmarkdown, plm, texreg

dplyr, rvest, readr, leaflet, stringr, ggplot2, sf, magrittr,
forcats, jsonlite, htmltools, purrr, xml2, curl, ggrepel,
scales, rlang, grDevices, httr

dplyr, rvest, readr, leaflet, stringr, ggplot2, sf, magrittr,
purrr, forcats, jsonlite, htmltools, xml2, curl, ggrepel,
scales, rlang, grDevices, httr

Search and download the data used in over 3,000 Our World in Data charts.
dplyr, rvest, readr, leaflet, stringr, ggplot2, sf, magrittr,
purrr, forcats, jsonlite, htmltools, xml2, curl, ggrepel,
scales, rlang, grDevices, httr, lifecycle

Generalized Linear Models Regularized with the Sorted L1-Norm
c(person("Johan", "Larsson", role = c("aut", "cre"),
email = "johan.larsson@stat.lu.se",
comment = c(ORCID = "0000-0002-4029-5945")),
person("Jonas",  "Wallin", role = "aut",
email = "jonas.wallin@stat.lu.se",
comment = c(ORCID = "0000-0003-0381-6593")),
person("Malgorzata", "Bogdan", role = "ctb",
comment = "code adapted from 'SLOPE'"),
person("Ewout", "van den Berg", role = "ctb",
comment = "code adapted from 'SLOPE'"),
person("Chiara", "Sabatti", role = "ctb",
comment = "code adapted from 'SLOPE'"),
person("Emmanuel", "Candes", role = "ctb",
comment = "code adapted from 'SLOPE'"),
person("Evan", "Patterson", role = "ctb",
comment = "code adapted from 'SLOPE'"),
person("Weijie", "Su", role = "ctb",
comment = "code adapted from 'SLOPE'"),
person("Jerome", "Friedman", role = "ctb",
comment = "code adapted from 'glmnet'"),
person("Trevor", "Hastie", role = "ctb",
comment = "code adapted from 'glmnet'"),
person("Rob", "Tibshirani", role = "ctb",
comment = "code adapted from 'glmnet'"),
person("Balasubramanian", "Narasimhan", role = "ctb",
comment = "code adapted from 'glmnet'"),
person("Noah", "Simon", role = "ctb",
comment = "code adapted from 'glmnet'"),
person("Junyang", "Qian", role = "ctb",
comment = "code adapted from 'glmnet'"))
Efficient implementations for Sorted L-One Penalized Estimation
(SLOPE): generalized linear models regularized with the
sorted L1-norm (Bogdan et al. (2015) <doi:10/gfgwzt>)
or, equivalently, ordered weighted L1-norm (OWL). Supported models include
ordinary least-squares regression, binomial regression, multinomial
regression, and Poisson regression. Both dense and sparse
predictor matrices are supported. In addition, the package features
predictor screening rules that enable fast and efficient solutions to
high-dimensional problems.
caret, covr, glmnet, knitr, rmarkdown, SLOPE, spelling,
testthat (>= 2.1.0)
Johan Larsson [aut, cre] (<https://orcid.org/0000-0002-4029-5945>),
Jonas Wallin [aut] (<https://orcid.org/0000-0003-0381-6593>),
Malgorzata Bogdan [ctb] (code adapted from 'SLOPE'),
Ewout van den Berg [ctb] (code adapted from 'SLOPE'),
Chiara Sabatti [ctb] (code adapted from 'SLOPE'),
Emmanuel Candes [ctb] (code adapted from 'SLOPE'),
Evan Patterson [ctb] (code adapted from 'SLOPE'),
Weijie Su [ctb] (code adapted from 'SLOPE'),
Jerome Friedman [ctb] (code adapted from 'glmnet'),
Trevor Hastie [ctb] (code adapted from 'glmnet'),
Rob Tibshirani [ctb] (code adapted from 'glmnet'),
Balasubramanian Narasimhan [ctb] (code adapted from 'glmnet'),
Noah Simon [ctb] (code adapted from 'glmnet'),
Junyang Qian [ctb] (code adapted from 'glmnet')