gpPosteriorSample: Plot Samples from a GP Posterior.

Description Usage Arguments See Also

View source: R/gpPosteriorSample.R

Description

Gaussian processes are non-parametric models. They are specified by their covariance function and a mean function. When combined with data observations a posterior Gaussian process is induced. This function samples from that posterior.

Usage

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  gpPosteriorSample( kernType, numSamps=10, params=NULL,
                     lims=c(-3,3), path=getwd(), png=FALSE )

Arguments

kernType

the type of kernel to sample from.

numSamps

the number of samples to take.

params

parameter vector for the kernel.

lims

limits of the x axis.

path

path where the plot images are saved.

png

save image as png.

See Also

gpOptions, kernCreate, kernCompute, gaussSamp, zeroAxes.


gptk documentation built on May 30, 2017, 6:41 a.m.