Author: Camilo Jose Torres-Jimenez [aut,cre], Alvaro Mauricio Montenegro Diaz [ths]
Maintainer: Camilo Jose Torres-Jimenez <cjtorresj@gmail.com>
Description: Density, distribution, quantile function, random number generation for the BMT (Bezier-Montenegro-Torres) distribution. Torres-Jimenez C.J. and Montenegro-Diaz A.M. (2017) <arXiv:1709.05534>. Moments, descriptive measures and parameter conversion for different parameterizations of the BMT distribution. Fit of the BMT distribution to non-censored data by maximum likelihood, moment matching, quantile matching, maximum goodness-of-fit, also known as minimum distance, maximum product of spacing, also called maximum spacing, and minimum quantile distance, which can also be called maximum quantile goodness-of-fit. Fit of univariate distributions for non-censored data using maximum product of spacing estimation and minimum quantile distance estimation is also included.
Packaged: 2017-09-19 02:51:31 UTC; cjtorresj

Title: Bayesian Approach for MTAR Models with Missing Data
Author: Valeria Bejarano Salcedo <vbejaranos@unal.edu.co>,
Sergio Alejandro Calderon Villanueva <sacalderonv@unal.edu.co>
Andrey Duvan Rincon Torres <adrincont@unal.edu.co>
Maintainer: Andrey Duvan Rincon Torres <adrincont@unal.edu.co>
Description: Implements parameter estimation using a Bayesian approach for Multivariate Threshold Autoregressive (MTAR) models with missing data using Markov Chain Monte Carlo methods. Performs the simulation of MTAR processes (mtarsim()), estimation of matrix parameters and the threshold values (mtarns()),  identification of the autoregressive orders using Bayesian variable selection (mtarstr()), identification of the number of regimes using Metropolised Carlin and Chib (mtarnumreg()) and estimate missing data, coefficients and covariance matrices conditional on the autoregressive orders, the threshold values and the number of regimes (mtarmissing()). Calderon and Nieto (2017) <doi:10.1080/03610926.2014.990758>.

Title: Bayesian Multi-Trait Multi-Environment for Genomic Selection
Authors@R: c(person("Francisco Javier", "Luna-Vazquez", email = "frahik@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-5370-7152")),
person("Fernando H.", "Toledo", role = "aut"),
person("Osval Antonio", "Montesinos-Lopez", email= "oamontes1@ucol.mx", role = "aut", comment = c(ORCID = "0000-0002-3973-6547")),
person("Abelardo", "Montesinos-Lopez", role = "aut"),
Maintainer: Francisco Javier Luna-Vazquez <frahik@gmail.com>
Description: Genomic selection and prediction models with the capacity to use multiple traits and environments, through ready-to-use Bayesian models. It consists a group of functions
that help to create regression models for some genomic models proposed by Montesinos-López, et al. (2016) <doi:10.1534/g3.116.032359>
Collate: BME.R BMTME.R BMTME_Package.R BMORS.R BMORSEnv.R cholesky.R
datasets.R detectCore.R RandomPartition.R RcppExports.R utils.R
Imports: BGLR, doSNOW, dplyr, foreach, matrixcalc, mvtnorm, progress,
Author: Francisco Javier Luna-Vazquez [aut, cre]