Maintainer: D. Scott Rinnan <scott.rinnan@yale.edu>
'enfa.R' 'exposure_map.R' 'names.R' 'overlay.R' 'parCov.R'

Description: Tools for climate- and ecological-niche factor analysis of spatial data, including methods for visualization of spatial variability of species sensitivity, exposure, and vulnerability to climate change. Processing of large files and parallel methods are supported. Climate-niche factor analysis is described in Rinnan and Lawler (2019) <doi:10.1111/ecog.03937>.
'enfa.R' 'exposure_map.R' 'overlay.R' 'parCov.R' 'parScale.R'

Title: Datasets of the CEO (Centre d'Estudis d'Opinio) for Opinion
person("Xavier", "Fernández-i-Marín", , "xavier.fim@gmail.com", role = c("aut", "cre"),
Description: Easy and convenient access to the datasets / microdata of the
"Centre d'Estudis d'Opinió", the catalan institution for polling and public
opinion.  The package uses the data stored in the servers of the CEO and returns
Depends: R (>= 4.1.0), haven, dplyr (>= 1.0.0), urltools, stringr,
Suggests: knitr, ggplot2, tidyr (> 1.1.1), curl, rmarkdown
Author: Xavier Fernández-i-Marín [aut, cre]

"Centre d'Estudis d'Opinió", the Catalan institution for polling and public
Suggests: knitr, R.rsp, ggplot2, tidyr (> 1.1.1), curl, rmarkdown,

Description: Easy and convenient access to the datasets of the
"Centre d'Estudis d'Opinio", the Catalan institution for polling and public
opinion. The package uses the data stored in the servers of the CEO and returns

Title: Causal Effect Random Forest of Interaction Tress
person(given = "Justin",family = "Thorp",email = "jjtthorp@gmail.com",role = c("aut","cre")),
person(given = "Luo",family = "Li",role = "aut"),
person(given = "Juanjuan", family = "Fan",role = "aut"))
Description: Fits a Causal Effect Random Forest of Interaction Tress (CERFIT) which is a modification of the Random Forest algorithm where each split is chosen to maximize subgroup treatment heterogeneity. Doing this allows it to estimate the individualized treatment effect for each observation in either randomized controlled trial (RCT) or observational data. For more information see X. Su, A. T. Peña, L. Liu, and R. A. Levine (2018) <doi:10.48550/arXiv.1709.04862>.
Imports: partykit, CBPS, randomForest, twang, Rcpp, stats, glmnet