runjags, tidyr (>= 0.5.1), HDInterval, ROCR
Packaged: 2019-12-14 20:58:41 UTC; shanascogin

Packaged: 2020-05-27 19:56:24 UTC; shanascogin

Imports: carData, caTools, coda (>= 0.13), dplyr (>= 0.5.0), ggplot2,
ggridges, reshape2, rlang, stats, texreg, tidyr (>= 0.5.1),
Suggests: brms, datasets, knitr, MCMCpack, rjags, R2jags, R2WinBUGS,
rmarkdown, rstan (>= 2.10.1), rstanarm, runjags, testthat, covr
Packaged: 2021-01-08 21:48:49 UTC; shanascogin

HDInterval, ROCR, graphics, grDevices, R2jags, runjags,
rstanarm, rjags, MCMCpack, R2WinBUGS, brms
Suggests: datasets, knitr, rmarkdown, rstan (>= 2.10.1), testthat, covr
Packaged: 2021-11-10 20:56:50 UTC; shanascogin

Title: Fast Projection Direction for Multivariate Changepoint Detection
Author: Georg Hahn [aut,cre], Paul Fearnhead [ctb], Idris A. Eckley [ctb]
Description: Implementations in 'cpp' of the BayesProject algorithm (see G. Hahn, P. Fearnhead, I.A. Eckley (2020) <doi:10.1007/s11222-020-09966-2>) which implements a fast approach to compute a projection direction for multivariate changepoint detection, as well as the sum-cusum and max-cusum methods, and a wild binary segmentation wrapper for all algorithms.

Title: Bayesian Robust Generalized Mixed Models for Longitudinal Data
Description: To perform model estimation using MCMC algorithms with Bayesian methods for incomplete longitudinal studies on binary outcomes that are measured repeatedly on subjects over time with drop-outs. Details about the method can be found in the vignette or <https://sites.google.com/view/kuojunglee/r-packages/bayesrgmm>.
Imports: Rcpp (>= 1.0.1), MASS, batchmeans, abind, reshape, msm,
Packaged: 2021-03-30 12:24:57 UTC; kuo-junglee
Author: Kuo-Jung Lee [aut, cre] (<https://orcid.org/0000-0002-7388-4738>),

Packaged: 2021-05-26 01:27:05 UTC; kuo-junglee

Description: To perform model estimation using MCMC algorithms with Bayesian methods for incomplete longitudinal studies on binary and ordinal outcomes that are measured repeatedly on subjects over time with drop-outs. Details about the method can be found in the vignette or <https://sites.google.com/view/kuojunglee/r-packages/bayesrgmm>.
Packaged: 2021-11-27 12:00:14 UTC; kuo-junglee