Title: Random Number Generation for Generalized Poisson Distributions
Description: Generation of univariate and multivariate data that follow the generalized Poisson distribution. The details of the method are explained in Demirtas (2017) <DOI:10.1080/03610918.2014.968725>.

Author: Hesen Li, Ruizhe Chen, Hai Nguyen, Yu-Che Chung, Ran Gao, Hakan Demirtas
Description: Generation of univariate and multivariate data that follow the generalized
Poisson distribution. The details of the univariate part are explained in
an extension of the correlated Poisson data generation routine that was introduced in
Yahav and Shmueli (2012) <doi: 10.1002/asmb.901>.

Title: Facilitates Analysis of CDC NHANES Data
person("Herb", "Susmann", email="susmann@silentspring.org", role=c("cre", "aut")),
person("Silent Spring Institute", role = "cph")
Description: Tools for downloading and analyzing CDC NHANES data, with a focus
Imports: foreign, survey, rvest, xml2, methods, dplyr

Title: Omnibus Test for Genetic Association Analysis using the Rank
Description: Implementation of genetic association tests that utilize the rank based inverse normal transformation (INT). The primary contribution is an omnibus test, which synthesizes two INT-based approaches, termed direct INT (DINT) and partially indirect INT (PIINT). In genome scale simulations, the omnibus test routinely provided valid inference against continuous phenotypes with skewed and heavy tailed residual distributions. Association testing against these same phenotypes via standard linear regression led to an excess of false positive associations. In addition to controlling the type I error, the omnibus approach provided power comparable to the more powerful of the component methods.
Imports: abind, cowplot, foreach, ggplot2, microbenchmark, mvtnorm,

Imports: abind, foreach, mvtnorm, RcppEigen
Suggests: cowplot, ggplot2, knitr, reshape2, rmarkdown

Description: Implementation of genetic association tests that utilize the rank based inverse normal transformation (INT). The primary contribution is an omnibus test, which synthesizes two complementary INT-based approaches. In simulations against phenotypes with skewed and heavy tailed residual distributions, the omnibus test provided valid inference in the absence of a genotypic effect, and provided power comparable to the more powerful of the component methods in the presence of a genotypic effect. Under these settings, standard linear regression often failed to control the type I error.
Imports: abind, foreach, mvtnorm, plyr, Rcpp
Suggests: ggplot2, knitr, reshape2, rmarkdown