Package: mlegp 3.1.9

Garrett M. Dancik

mlegp: Maximum Likelihood Estimates of Gaussian Processes

Maximum likelihood Gaussian process modeling for univariate and multi-dimensional outputs with diagnostic plots following Santner et al (2003) <doi:10.1007/978-1-4757-3799-8>. Contact the maintainer for a package version that includes sensitivity analysis.

Authors:Garrett M. Dancik

mlegp_3.1.9.tar.gz
mlegp_3.1.9.tar.gz(r-4.5-noble)mlegp_3.1.9.tar.gz(r-4.4-noble)
mlegp_3.1.9.tgz(r-4.4-emscripten)mlegp_3.1.9.tgz(r-4.3-emscripten)
mlegp.pdf |mlegp.html
mlegp/json (API)

# Install 'mlegp' in R:
install.packages('mlegp', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblas

4.74 score 1 stars 22 packages 73 scripts 1.2k downloads 1 mentions 41 exports 0 dependencies

Last updated 3 years agofrom:48bc5f5814. Checks:OK: 1 NOTE: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 07 2024
R-4.5-linux-x86_64NOTEDec 07 2024

Exports:anyRepscalcCorOneObscalcLogLikeManualcalcPredictionErrorcalcPredictionErrorCVcalcVarMatrixcreateGPcreateWindowCVestimateNuggetfitGPfromRgetSingularValuesgp.listgpDimgpObsis.gpis.gp.listmatchIndexesmlegpmlegp2numSingularValuespcweightsplot.gpplot.gp.listplotObservedEffectsplotObservedEffects.gpplotObservedEffectsDefaultpredict.gppredictMupredictNewYCVpredictNewZprint.gpprint.gp.listsetGPNamessetParamssingularValueImportancesummary.gpsummary.gp.listtoParamIndexesuniqueSummaryvarPerReps

Dependencies:

Full User Manual

Rendered frommlegp.Rnwusingutils::Sweaveon Dec 07 2024.

Last update: 2018-01-30
Started: 2018-01-30