Package: GaSP
Type: Package
Title: Train and Apply a Gaussian Stochastic Process Model
Version: 1.0.6
Authors@R: c(
    person(given = "William J.",
           family = "Welch",
           role = c("aut", "cre", "cph"),
           email = "will@stat.ubc.ca",
           comment = c(ORCID = "0000-0002-4575-3124")),
    person(given = "Yilin",
           family = "Yang",
           role = c("aut"),
           email = "yangyl17@students.cs.ubc.ca",
           comment = c(ORCID = "0000-0003-0885-6017"))
           )
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, <doi:10.1214/ss/1177012413>.  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", <doi:10.1007/0-387-28014-6_14>.
Depends: R (>= 3.5.0)
Suggests: markdown, rmarkdown, knitr, testthat
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.1
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2024-06-24 17:46:14 UTC; will
Author: William J. Welch [aut, cre, cph]
    (<https://orcid.org/0000-0002-4575-3124>),
  Yilin Yang [aut] (<https://orcid.org/0000-0003-0885-6017>)
Maintainer: William J. Welch <will@stat.ubc.ca>
Repository: CRAN
Date/Publication: 2024-06-27 09:10:02 UTC
Built: R 4.6.0; aarch64-apple-darwin23; 2026-04-25 19:08:14 UTC; unix
Archs: GaSP.so.dSYM
