demAutoOptimiseGp: Gaussian Process Optimisation Demo

Description Usage Arguments See Also

Description

Shows that by varying the length scale, an artificial data set has different likelihoods, yet there is an optimum for which the likelihood is maximised. This demo is similar to demOptimiseGp, only here, it is demonstrated how the length scale hyperparameter is optimised automatically through SCG (scaled conjugate gradients) numerical optimisation. Run multiple times to understand the effect of optimisation on randomly generated datasets.

Usage

1
  demAutoOptimiseGp(path=getwd(), filename='demAutoOptimiseGp', png=FALSE, gif=FALSE)

Arguments

path

path where the plot images are saved.

filename

name of saved images.

png

save image as png.

gif

save series of images as animated gif.

See Also

gpOptions, kernCreate, gaussSamp, gpCreate, gpExpandParam, gpLogLikelihood, gpPosteriorMeanVar, gpOptimise, gpPlot.


gptk documentation built on May 2, 2019, 3:27 p.m.

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