Package: mlegp 3.1.9
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:
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')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:48bc5f5814. Checks:OK: 1 NOTE: 1. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 07 2024 |
R-4.5-linux-x86_64 | NOTE | Dec 07 2024 |
Exports:anyRepscalcCorOneObscalcLogLikeManualcalcPredictionErrorcalcPredictionErrorCVcalcVarMatrixcreateGPcreateWindowCVestimateNuggetfitGPfromRgetSingularValuesgp.listgpDimgpObsis.gpis.gp.listmatchIndexesmlegpmlegp2numSingularValuespcweightsplot.gpplot.gp.listplotObservedEffectsplotObservedEffects.gpplotObservedEffectsDefaultpredict.gppredictMupredictNewYCVpredictNewZprint.gpprint.gp.listsetGPNamessetParamssingularValueImportancesummary.gpsummary.gp.listtoParamIndexesuniqueSummaryvarPerReps
Dependencies:
Readme and manuals
Help Manual
Help page | Topics |
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mlegp package | mlegp-package |
Gaussian Process and Gaussian Process Lists | is.gp is.gp.list |
mlegp: maximum likelihood estimation of Gaussian process parameters | fitGPfromR mlegp mlegp2 |
Gaussian Process Nugget Related Functions | anyReps estimateNugget nugget varPerReps |
Diagnostic Plots for Gaussian processes | plot.gp |
Diagnostics Plots for Gaussian Process Lists | plot.gp.list |
Plot Observed Values Vs. Each Dimension of the Design Matrix | plotObservedEffects plotObservedEffects.gp plotObservedEffectsDefault |
Gaussian Process Predictions | calcPredictionError predict.gp predict.gp.list predictMu predictNewZ |
Gaussian Process Summary Information | print.gp |
Gaussian Process List Summary Information | print.gp.list |
Gaussian Process Summary Information | summary.gp |
Gaussian Process List Summary Information | summary.gp.list |
Summary of outputs for each unique input | uniqueSummary |