A framework with tools to compare two random variables, and determine which of takes produces lower values. See the README.md at <https://github.com/EtorArza/RVCompare> for a quick start guide. It can compute the Cp and Cd of two probability distributions, as explained in E. Arza (2021) <https://github.com/EtorArza/RVCompare-paper/releases>. Given the observed samples of two random variables X_A and X_B, it can compute the cumulative difference-plot (see E. Arza (2021) <https://github.com/EtorArza/RVCompare-paper/releases> for details). Uses bootstrap and DKW-bounds to compute the confidence bands of the cumulative distributions. These two methods are described in B. Efron. (1979) <doi:10.1214/aos/1176344552> and P. Massart (1990) <doi:10.1214/aop/1176990746>.

A framework with tools to compare two random variables, and determine which of takes produces lower values. See the README.md at <https://github.com/EtorArza/RVCompare> for a quick start guide. It can compute the Cp and Cd of two probability distributions, as explained in E. Arza (2021) <doi:10.48550/arXiv.2203.07889>. Given the observed samples of two random variables X_A and X_B, it can compute the cumulative difference-plot (see E. Arza (2021) <> for details). Uses bootstrap and DKW-bounds to compute the confidence bands of the cumulative distributions. These two methods are described in B. Efron. (1979) <doi:10.1214/aos/1176344552> and P. Massart (1990) <doi:10.1214/aop/1176990746>.

Rare Variants Association Analyses with Family Data
coxme, survival, lme4, kinship2, MASS, Matrix
The RVFam package provides functions to perform single SNP association analyses and gene-based tests for continuous, binary and survival traits against sequencing data (e.g. exome chip) using family data.

c(
person(given = "Peter",
family = "Kochunov",
role = c("aut"),
email = "pkochunov@gmail.com"),
person(given = "Si",
family = "Gao",
role = c("aut", "cre"),
email = "sgao@som.umaryland.edu"),
person(given = "Fatima",
family = "Talib",
role = c("aut"),
email = "fatal1@umbc.edu")
)
The Regional Vulnerability Index (RVI), a statistical measure of brain structural abnormality, quantifies an individual’s similarity to the expected pattern of deficits in schizophrenia (Kochunov P, Fan F, Ryan MC, et al. (2020) <doi:10.1002/hbm.25045>).
Peter Kochunov [aut],
Si Gao [aut, cre],
Fatima Talib [aut]