Perform classic chi-squared tests and Ripol et al(1999)
             binomial confidence interval approach for autopolyploid
             dominant markers. Also, dominant markers may be generated
             for families of offspring where either one or both of the
             parents possess the marker. Missing values and
             misclassified markers may be generated at random.

Fits Bayesian mixture models to estimate marker dosage for dominant markers in autopolyploids using JAGS (1.0 or greater) as outlined in Baker et al "Bayesian estimation of marker dosage in sugarcane and other autopolyploids" (2010, <doi:10.1007/s00122-010-1283-z>). May be used in conjunction with polySegratio for simulation studies and comparison with standard methods.

Given a data matrix with rows representing data vectors and columns representing variables, produces a directed polytree for the underlying causal structure. Based on the algorithm developed in Chatterjee and Vidyasagar (2022) <arxiv:2209.07028>. The method is fully nonparametric, making no use of linearity assumptions, and especially useful when the number of variables is large.

Routines for flexible functional form estimation via basis
    regression, with model selection via the adaptive LASSO or SCAD to prevent
    overfitting.

Provides functions to compute and plot power levels, minimum detectable effect sizes, and minimum required sample sizes for the test of the overall average effect size in meta-analysis of dependent effect sizes.

POM-aSPU test evaluates an association between an ordinal response and multiple phenotypes, for details see Kim and Pan (2017) <DOI:10.1002/gepi.22033>.

Implements the method described at the UCLA Statistical
    Consulting site <https://stats.idre.ucla.edu/r/dae/ordinal-logistic-regression/>
    for checking if the proportional odds assumption holds for a 
    cumulative logit model.

Provides the infrastructure to define and analyze the solutions of Partially Observable Markov Decision Process (POMDP) models. Interfaces for various exact and approximate solution algorithms are available including value iteration, point-based value iteration and SARSOP. Hahsler and Cassandra <doi:10.32614/RJ-2024-021>.