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binaryGP  

Fit and Predict a Gaussian Process Model with (Time-Series) Binary Response
View on CRAN: Click here


Download and install binaryGP package within the R console
Install from CRAN:
install.packages("binaryGP")

Install from Github:
library("remotes")
install_github("cran/binaryGP")

Install by package version:
library("remotes")
install_version("binaryGP", "0.2")



Attach the package and use:
library("binaryGP")
Maintained by
Chih-Li Sung
[Scholar Profile | Author Map]
First Published: 2017-09-19
Latest Update: 2017-09-19
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) .
How to cite:
Chih-Li Sung (2017). binaryGP: Fit and Predict a Gaussian Process Model with (Time-Series) Binary Response. R package version 0.2, https://cran.r-project.org/web/packages/binaryGP. Accessed 29 Mar. 2025.
Previous versions and publish date:
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Complete documentation for binaryGP
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