Constructs multiple graphs, plotting each parameter from the design matrix on the x-axis and observations on the y-axis
an object of class
if x is a design matrix, a vector of observations;
if x is of class
x is NOT of class
x is a design matrix), all columns of
x will be plotted separately against the vector of observations
x is of class
gp, the specified columns of the design matrix of
x will be plotted against the the observations
It is often useful to use this function before fitting the gaussian process, to check that the observations are valid
Garrett M. Dancik firstname.lastname@example.org
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## create the design and output matrices ## x1 = kronecker(seq(0,1,by=.25), rep(1,5)) x2 = rep(seq(0,1,by=.25),5) z = 4 * x1 - 2*x2 + x1 * x2 + rnorm(length(x1), sd = 0.001) ## look at the observed effects prior to fitting the GP ## plotObservedEffects(cbind(x1,x2), z) ## fit the Gaussian process ## fit = mlegp(cbind(x1,x2), z, param.names = c("x1", "x2")) ## look at the observed effects of the fitted GP (which are same as above) plotObservedEffects(fit)
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