Package: mlegp 3.1.10
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_3.1.10.tar.gz
mlegp_3.1.10.tar.gz(r-4.7-arm64)mlegp_3.1.10.tar.gz(r-4.7-x86_64)mlegp_3.1.10.tar.gz(r-4.6-arm64)mlegp_3.1.10.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
card.svg |card.png
mlegp/json (API)
| # Install 'mlegp' in R: |
| install.packages('mlegp', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/gdancik/mlegp/issues
Last updated from:c7d3ba75b9. Checks:5 OK, 1 FAIL. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 104 | ||
| linux-devel-x86_64 | OK | 105 | ||
| source / vignettes | OK | 170 | ||
| linux-release-arm64 | OK | 104 | ||
| linux-release-x86_64 | OK | 118 | ||
| wasm-release | FAIL | 86 |
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 |
|---|---|
| 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 |
