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
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: 2026-10-08 08:23:41 UTC; root
Config/pak/sysreqs: cmake
Repository: https://chihli.r-universe.dev
Date/Publication: 2017-09-19 07:34:21 UTC
RemoteUrl: https://github.com/cran/binaryGP
RemoteRef: HEAD
RemoteSha: db687284179ec887cdf33407c7773b3040dcc8b7