Analysis of experimental multi-parent populations to detect regions
             of the genome (called quantitative trait loci, QTLs) influencing
             phenotypic traits measured in unique and multiple environments.
             The population must be composed of crosses between a set of at
             least three parents (e.g. factorial design, 'diallel', or nested
             association mapping). The functions cover data processing,
             QTL detection, and results visualization. The implemented methodology
             is described in Garin, Wimmer, Mezmouk, Malosetti and van Eeuwijk (2017)
             <doi:10.1007/s00122-017-2923-3>, in Garin, Malosetti
             and van Eeuwijk (2020) <doi: 10.1007/s00122-020-03621-0>,
             and in Garin, Diallo, Tekete, Thera, ..., and Rami (2024) <doi: 10.1093/genetics/iyae003>.

Fitting Multi-Parameter Regression (MPR) models to right-censored survival data. These are flexible parametric regression models which extend standard models, for example, proportional hazards. See Burke & MacKenzie (2016) <doi:10.1111/biom.12625> and Burke et al (2020) <doi:10.1111/rssc.12398>.

Developed for computing the probability density function, computing the cumulative distribution function, computing the quantile function, random generation, drawing q-q plot, and estimating the parameters of 24 G-family of statistical distributions via the maximum product spacing approach introduced in <https://www.jstor.org/stable/2345411>. The set of families contains: beta G distribution, beta exponential G distribution, beta extended G distribution, exponentiated G distribution, exponentiated exponential Poisson G distribution, exponentiated generalized G distribution, exponentiated Kumaraswamy G distribution, gamma type I G distribution, gamma type II G distribution, gamma uniform G distribution, gamma-X generated of log-logistic family of G distribution, gamma-X family of modified beta exponential G distribution, geometric exponential Poisson G distribution, generalized beta G distribution, generalized transmuted G distribution, Kumaraswamy G distribution, log gamma type I G distribution, log gamma type II G distribution, Marshall Olkin G distribution, Marshall Olkin Kumaraswamy G distribution, modified beta G distribution, odd log-logistic G distribution, truncated-exponential skew-symmetric G distribution, and Weibull G distribution.