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
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mlegp.pdf |mlegp.html✨
mlegp/json (API)
| # Install 'mlegp' in R: |
| install.packages('mlegp', repos = c('https://gdancik.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/gdancik/mlegp/issues
Last updated 2 years agofrom:7ceb482830. Checks:OK: 1 NOTE: 8. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 21 2024 |
| R-4.5-win-x86_64 | NOTE | Oct 21 2024 |
| R-4.5-linux-x86_64 | NOTE | Oct 21 2024 |
| R-4.4-win-x86_64 | NOTE | Oct 21 2024 |
| R-4.4-mac-x86_64 | NOTE | Oct 21 2024 |
| R-4.4-mac-aarch64 | NOTE | Oct 21 2024 |
| R-4.3-win-x86_64 | NOTE | Oct 21 2024 |
| R-4.3-mac-x86_64 | NOTE | Oct 21 2024 |
| R-4.3-mac-aarch64 | NOTE | Oct 21 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 |
|---|---|
| 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 |
