binaryGP: Fit and Predict a Gaussian Process Model with (Time-Series) Binary Response

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>.

Getting started

Package details

AuthorChih-Li Sung
MaintainerChih-Li Sung <>
LicenseGPL-2 | GPL-3
Package repositoryView on CRAN
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binaryGP documentation built on May 1, 2019, 8:03 p.m.