binaryGP: Fit and Predict a Gaussian Process Model with (Time-Series) Binary Response
Version 0.2

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) .

Getting started

Package details

AuthorChih-Li Sung
Date of publication2017-09-19 08:34:21 UTC
MaintainerChih-Li Sung <[email protected]>
LicenseGPL-2 | GPL-3
Package repositoryView on CRAN
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binaryGP documentation built on Sept. 19, 2017, 9:02 a.m.