Simple Conjoint Tidying, Analysis, and Visualization
Simple tidying, analysis, and visualization of conjoint (factorial) experiments, including estimation and visualization of average marginal component effects ('AMCEs') and marginal means ('MMs') for weighted and un-weighted survey data, along with useful reference category diagnostics and statistical tests. Estimation of 'AMCEs' is based upon methods described by Hainmueller, Hopkins, and Yamamoto (2014) <doi:10.1093/pan/mpt024>.
stats, sandwich (>= 2.4-0), survey (>= 3.33), lmtest, ggplot2
(>= 2.0), ggstance, scales

c(
person("Thomas J.", "Leeper", role = c("aut", "cre"),
email = "thosjleeper@gmail.com",
comment = c(ORCID = "0000-0003-4097-6326")),
person("Matthew", "Barnfield", role = "ctb",
email = "m.barnfield@qmul.ac.uk"))
stats, sandwich (>= 2.4-0), survey (>= 3.33), lmtest, ggplot2
(>= 2.0), ggstance, scales, utils
Thomas J. Leeper [aut, cre] (<https://orcid.org/0000-0003-4097-6326>),
Matthew Barnfield [ctb]

A Probabilistic Approach to Reconstruct Past Climates Using
Biological Climate Proxies
person(given = "Manuel",
family = "Chevalier",
role = c("aut", "cre"),
email = "chevalier.manuel@gmail.com",
comment = c(ORCID = "0000-0002-8183-9881"))
Applies the CREST climate reconstruction
method. It can be used using the calibration data that can be obtained
through the package or by importing private data. An ensemble of
graphical outputs were designed to facilitate the use of the
package and the interpretation of the results. More information can
be found form Chevalier (2021) <doi:10.5194/cp-2021-153>.
clipr, DBI, methods, plyr, raster, rgdal, rgeos, RPostgres,
scales, sp, stringr, viridis
knitr, openxlsx, plot3D, rmarkdown, pals
Manuel Chevalier [aut, cre] (<https://orcid.org/0000-0002-8183-9881>)

A Probabilistic Approach to Reconstruct Past Climates Using
Palaeoecological Datasets
Applies the CREST climate reconstruction
method. It can be used using the calibration data that can be obtained
through the package or by importing private data. An ensemble of
graphical outputs were designed to facilitate the use of the
package and the interpretation of the results. More information can
be obtained from Chevalier (2022) <doi:10.5194/cp-18-821-2022>.