A Gaussian or Student's t copula-based procedure for generating samples from discrete random variables with prescribed correlation matrix and marginal distributions.

Functions for whole-genome sequencing studies, including genome-wide scan, candidate region scan and single window test.

Genotyping of triploid individuals from luminescence data (marker probeset A and B). Works also for diploids.
	Two main functions: Run_Clustering() that regroups individuals with a same genotype based on proximity and
	Run_Genotyping() that assigns a genotype to each cluster. For Shiny interface use: launch_GenoShiny().

Sequential change-point tests, parameters estimation, and goodness-of-fit tests for generalized Ornstein-Uhlenbeck processes.

It provides an interesting solution for handling a high number 
	of segmentation variables in partial least squares structural equation 
	modeling. The package implements the "Pathmox" algorithm (Lamberti, Sanchez, 
	and Aluja,(2016)<doi:10.1002/asmb.2168>) including the F-coefficient 
	test (Lamberti, Sanchez, and Aluja,(2017)<doi:10.1002/asmb.2270>) 
	to detect the path coefficients responsible for the identified differences). 
	The package also allows running the hybrid multi-group approach (Lamberti (2021) 
	<doi:10.1007/s11135-021-01096-9>).

Power and sample size calculations for genetic association studies allowing 
    for misspecification of the model of genetic susceptibility.
    "Hum Hered. 2019;84(6):256-271.<doi:10.1159/000508558>. Epub 2020 Jul 28."
    Power and/or sample size can be calculated for logistic (case/control study design) 
    and linear (continuous phenotype) regression models, using additive, dominant, 
    recessive or degree of freedom coding of the genetic covariate while assuming 
    a true dominant, recessive or additive genetic effect. In addition, power and 
    sample size calculations can be performed for gene by environment interactions.  
    These methods are extensions of Gauderman (2002) 
    <doi:10.1093/aje/155.5.478> and Gauderman (2002) <doi:10.1002/sim.973>
    and are described in: 
    Moore CM, Jacobson S, Fingerlin TE. Power and Sample Size Calculations 
    for Genetic Association Studies in the Presence of Genetic Model Misspecification. 
    American Society of Human Genetics. 
    October 2018, San Diego.