Learn R Programming

mlegp (version 3.1.9)

Maximum Likelihood Estimates of Gaussian Processes

Description

Maximum likelihood Gaussian process modeling for univariate and multi-dimensional outputs with diagnostic plots following Santner et al (2003) . Contact the maintainer for a package version that includes sensitivity analysis.

Copy Link

Version

Install

install.packages('mlegp')

Monthly Downloads

1,342

Version

3.1.9

License

GPL (>= 2)

Maintainer

Garrett M Dancik

Last Published

March 10th, 2022

Functions in mlegp (3.1.9)

mlegp-internal

Internal Functions for Gaussian Processes
gp.list

Gaussian Process Lists
plot.gp.list

Diagnostics Plots for Gaussian Process Lists
mlegp-nugget-related

Gaussian Process Nugget Related Functions
summary.gp.list

Gaussian Process List Summary Information
plot.gp

Diagnostic Plots for Gaussian processes
summary.gp

Gaussian Process Summary Information
mlegp

mlegp: maximum likelihood estimation of Gaussian process parameters
createWindow

Gaussian Process Plotting Functions
mlegp-parameter-lookup

Parameter Lookup Functions
CV

Gaussian process cross-validation
plotObservedEffects

Plot Observed Values Vs. Each Dimension of the Design Matrix
createGP

creates a Gaussian process object
predict.gp

Gaussian Process Predictions
mlegp-naming-functions

mlegp naming functions
uniqueSummary

Summary of outputs for each unique input
print.gp

Gaussian Process Summary Information
mlegp-package

mlegp package
print.gp.list

Gaussian Process List Summary Information
is.gp

Gaussian Process and Gaussian Process Lists
mlegp-svd-functions

Singular Value Decomposition functions for mlegp