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GaSP  

Train and Apply a Gaussian Stochastic Process Model
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("GaSP", "1.0.6")



Attach the package and use:
library("GaSP")
Maintained by
William J. Welch
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-06-07
Latest Update: 2023-12-08
Description:
Train a Gaussian stochastic process model of an unknown function, possibly observed with error, via maximum likelihood or maximum a posteriori (MAP) estimation, run model diagnostics, and make predictions, following Sacks, J., Welch, W.J., Mitchell, T.J., and Wynn, H.P. (1989) "Design and Analysis of Computer Experiments", Statistical Science, . Perform sensitivity analysis and visualize low-order effects, following Schonlau, M. and Welch, W.J. (2006), "Screening the Input Variables to a Computer Model Via Analysis of Variance and Visualization", .
How to cite:
William J. Welch (2021). GaSP: Train and Apply a Gaussian Stochastic Process Model. R package version 1.0.6, https://cran.r-project.org/web/packages/GaSP. Accessed 12 Nov. 2024.
Previous versions and publish date:
1.0.0 (2021-06-07 11:40), 1.0.1 (2022-01-18 08:42), 1.0.4 (2023-05-18 13:12), 1.0.5 (2023-12-08 07:30)
Other packages that cited GaSP R package
View GaSP citation profile
Other R packages that GaSP depends, imports, suggests or enhances
Complete documentation for GaSP
Functions, R codes and Examples using the GaSP R package
Full GaSP package functions and examples
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