Package: binaryGP
Type: Package
Title: Fit and Predict a Gaussian Process Model with (Time-Series)
        Binary Response
Version: 0.2
Date: 2017-09-17
Author: Chih-Li Sung
Maintainer: Chih-Li Sung <iamdfchile@gmail.com>
Description: Allows the estimation and prediction for binary Gaussian process model. The mean function can be assumed to have time-series structure. The estimation methods for the unknown parameters are based on penalized quasi-likelihood/penalized quasi-partial likelihood and restricted maximum likelihood. The predicted probability and its confidence interval are computed by Metropolis-Hastings algorithm. More details can be seen in Sung et al (2017) <arXiv:1705.02511>.
License: GPL-2 | GPL-3
LazyData: TRUE
Imports: Rcpp (>= 0.12.0), lhs (>= 0.10), logitnorm (>= 0.8.29), nloptr
        (>= 1.0.4), GPfit (>= 1.0-0), stats, graphics, utils, methods
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 5.0.1
Depends: R (>= 2.14.1)
NeedsCompilation: yes
Packaged: 2017-09-18 16:24:05 UTC; apple
Repository: CRAN
Date/Publication: 2017-09-19 08:34:21 UTC
Built: R 4.6.0; aarch64-apple-darwin23; 2026-04-25 23:57:16 UTC; unix
Archs: binaryGP.so.dSYM
