gpPosteriorSample: Plot Samples from a GP Posterior.

In gptk: Gaussian Processes Tool-Kit

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

  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 2, 2019, 3:27 p.m.