Package: magp
Title: Mapping-Based Additive Gaussian Process Models
Version: 0.8.0
Authors@R: c(
    person("Tony", "Wang", email = "wangtony883@gmail.com",
           role = c("aut", "cre", "cph")),
    person("Qian", "Xiao", role = c("aut", "cph")),
    person("Yaping", "Wang", role = "cph"),
    person("Abhyuday", "Mandal", role = "cph"),
    person("Xinwei", "Deng", role = "cph"))
Description: Fits mapping-based additive Gaussian process models for
    experiments in which each component has both a quantitative level and a
    position in an ordered sequence. Two model structures are available: a
    compact two-dimensional mapping and a full mapping with one fewer
    dimension than the number of components. Both models support parameter
    estimation, point prediction, and plug-in predictive uncertainty. Input
    checks validate the sequence data and apply consistent scaling to the
    quantitative inputs. Computationally intensive covariance and gradient
    calculations are implemented in C++ with 'Rcpp'. The model was introduced
    by Xiao et al. (2024) <doi:10.1080/01621459.2022.2123335>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: Rcpp, nloptr, stats
LinkingTo: Rcpp
Suggests: testthat (>= 3.0.0)
Config/testthat/edition: 3
NeedsCompilation: yes
RoxygenNote: 7.3.3
Packaged: 2026-08-22 03:51:29 UTC; skr
Author: Tony Wang [aut, cre, cph],
  Qian Xiao [aut, cph],
  Yaping Wang [cph],
  Abhyuday Mandal [cph],
  Xinwei Deng [cph]
Maintainer: Tony Wang <wangtony883@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-03 11:40:09 UTC
Built: R 4.5.2; aarch64-apple-darwin20; 2026-09-03 12:53:27 UTC; unix
Archs: magp.so.dSYM
