caret, doParallel, dplyr, ggplot2,foreach, httr, magrittr,
methods, plotROC, plyr, raster, reshape2, sp, leaflet

Calibrates and Reweights Units in Samples
Provides user-friendly tools for calibration in survey sampling. The package is production-oriented, and its interface is inspired by the famous popular macro 'Calmar' for SAS, so that 'Calmar' users can quickly get used to 'icarus'. In addition to calibration (with linear, raking and logit methods), 'icarus' features functions for calibration on tight bounds and penalized calibration.
c(person("Antoine Rebecq", role=c("aut","cre"),
email = "antoine.rebecq@m4x.org"))

Provides user-friendly tools for calibration in survey sampling.
The package is production-oriented, and its interface is inspired by the famous
popular macro 'Calmar' for SAS, so that 'Calmar' users can quickly get used to
'icarus'. In addition to calibration (with linear, raking and logit methods),
'icarus' features functions for calibration on tight bounds and penalized
calibration.

testthat, ggplot2, Rglpk, slam, xtable, magrittr

Intraclass Correlation Coefficient for Count Data
glmmTMB, ggplot2, Deriv, gridExtra, VGAM, dplyr
Estimates the intraclass correlation coefficient (ICC) for count data to assess repeatability (intra-methods concordance) and concordance (between-method concordance). In the concordance setting, the ICC is equivalent to the concordance correlation coefficient estimated by variance components. The ICC is estimated using the estimates from generalized linear mixed models. The within-subjects distributions considered are: Poisson; Negative Binomial with additive and proportional extradispersion; Zero-Inflated Poisson; and Zero-Inflated Negative Binomial with additive and proportional extradispersion. The statistical methodology used to estimate the ICC with count data can be found in Carrasco (2010) <doi:10.1111/j.1541-0420.2009.01335.x>.

Multilevel Model Intraclass Correlation for Slope Heterogeneity
c(person("Steven Andrew", "Culpepper", role = c("aut", "cph","cre"),
email = "sculpepp@illinois.edu"),
person("Herman", "Aguinis", role = c("aut", "cph"), email =
"haguinis@gwu.edu"))
A function and vignettes for computing an intraclass correlation
described in Aguinis & Culpepper (2015) <doi:10.1177/1094428114563618>.
This package quantifies the share of variance in a dependent variable that
is attributed to group heterogeneity in slopes.
Steven Andrew Culpepper [aut, cph, cre],
Herman Aguinis [aut, cph]