predict the expected values and posterior distributions of the Gaussian Process
1 | gp_predict(gp, x_predict, burnin = 0, thin = 1, covs = FALSE)
|
gp |
a fit of the gaussian process from gp_mcmc |
x_predict |
the values at which we desire predictions |
burnin |
length of sequence to discard as a transient |
thin |
frequency of sub-sampling (make posterior distribution smaller if necessary) |
covs |
if TRUE, return covariances instead of variances (set high thinning as this is memory intensive) |
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