Package: baymvb
Version: 1.0.3
Title: Bayesian analysis of multivariate binary data
Author: S M Mwalili <samuel_mwalili@yahoo.com>
Maintainer: S M Mwalili <samuel_mwalili@yahoo.com>
Description: This package fits multivariate binary data
using Bayesian approach
License: GPL Version 2 or later.
Packaged: Sun Oct  2 00:48:10 2005; Samuel

Package: baymvb
Version: 1.0.4
Title: Bayesian analysis of multivariate binary data
Author: S M Mwalili <samuel_mwalili@yahoo.com>
Maintainer: S M Mwalili <samuel_mwalili@yahoo.com>
Description: This package fits multivariate binary data
using Bayesian approach
License: GPL Version 2 or later.
Packaged: Thu Oct  6 14:54:40 2005; Samuel

Title: Bayesian fitting of Ornstein-Uhlenbeck models to phylogenies
Author: Josef C. Uyeda, Jon Eastman and Luke Harmon
Maintainer: Josef C. Uyeda <josef.uyeda@gmail.com>
Description: Tools for fitting and simulating multi-optima Ornstein-Uhlenbeck
models to phylogenetic comparative data using Bayesian reversible-jump
Imports: Rcpp (>= 0.10.3), MASS, mnormt, fitdistrplus, denstrip

Title: Bayesian Fitting of Ornstein-Uhlenbeck Models to Phylogenies
Imports: Rcpp (>= 0.10.3), MASS, mnormt, fitdistrplus, denstrip,

assertthat, foreach, Matrix, graphics, grDevices, stats

Title: Bayesian Stability Analysis of Genotype by Environment
, person(c("Juan", "Burgueño"),  email = "j.crossa@cgiar.org", role = c("aut", "ctb"))
Description: Performs general Bayesian estimation method of linear–bilinear models for genotype × environment interaction. The method is explained in Perez-Elizalde, S., Jarquin, D., and Crossa, J. (2011) (<doi:10.1007/s13253-011-0063-9>).
Imports: dplyr, ggplot2, ggfortify, lme4, magrittr, MASS, matrixStats,
reshape2, rstiefel, rlang, scales, stats, tibble, tidyr,

Title: Long Term Water Quality Trend Analysis
Description: Enable users to evaluate long-term trends using a Generalized
Additive Modeling (GAM) approach. The model development includes selecting a
GAM structure to describe nonlinear seasonally-varying changes over time,
incorporation of hydrologic variability via either a river flow or salinity,
the use of an intervention to deal with method or laboratory changes
suspected to impact data values, and representation of left- and
interval-censored data. The approach has been applied to water quality data
in the Chesapeake Bay, a major estuary on the east coast of the United
States to provide insights to a range of management- and research-focused
Author: Rebecca Murphy, Elgin Perry, Jennifer Keisman, Jon Harcum, Erik W Leppo
Suggests: devtools, fitdistrplus, imputeTS, knitr, nlme, pander,
Imports: XML, dataRetrieval, digest, gdata, memoise, methods, plyr,