likelihood.plot: Plot the concentrated likelihood of an SSM.

In SSM: Fit and Analyze Smooth Supersaturated Models

Description

Plot the concentrated likelihood used to estimate the parameters of the metamodel error estimating Gaussian process.

Usage

likelihood.plot(ssm, xrange = c(0, 1000), grid = 200)

Arguments

ssm	An SSM object.
xrange	(optional) The range of the x axis. Set to c(0, 1000) by default.
grid	(optional) A number. The number of points used to plot the curve.

Details

As a diagnostic it can be helpful to look at the concentrated likelihood function of the correlation function used to estimate the metamodel error. Flat likelihood functions make it difficult to pick a suitable r length parameter. Note that r and sigma can be set manually.

Examples

data(attitude)
X <- transform11(attitude[ 2:7])
Y <- attitude[ , 1]
s <- fit.ssm(X, Y, GP = TRUE)
likelihood.plot(s)
likelihood.plot(s, xrange = c(0, 20))

SSM documentation built on May 1, 2019, 10:09 p.m.