plot: Plots object from 'bhetGP' package

In bhetGP: Bayesian Heteroskedastic Gaussian Processes

Plots object from bhetGP package

Description

Acts on a bhetgp, bhetgp_vec, bhomgp or, bhomgp_vec object. Generates trace plots for log likelihood of mean and noise process, length scales of corresponding processes, scale parameters and the nuggets. Generates plots of hidden layers for one-dimensional inputs. Generates plots of the posterior mean and estimated 90% prediction intervals for one-dimensional inputs; generates heat maps of the posterior mean and point-wise variance for two-dimensional inputs.

Usage

## S3 method for class 'bhetgp'
plot(x, trace = NULL, predict = NULL, verb = TRUE, ...)

## S3 method for class 'bhomgp'
plot(x, trace = NULL, predict = NULL, verb = TRUE, ...)

## S3 method for class 'bhetgp_vec'
plot(x, trace = NULL, predict = NULL, verb = TRUE, ...)

## S3 method for class 'bhomgp_vec'
plot(x, trace = NULL, predict = NULL, verb = TRUE, ...)

Arguments

x	object of class bhetgp, bhetgp_vec, bhomgp, or bhomgp_vec
trace	logical indicating whether to generate trace plots (default is TRUE if the object has not been through predict)
predict	logical indicating whether to generate posterior predictive plot (default is TRUE if the object has been through predict)
verb	logical indicating whether to print plot.
...	N/A

Details

Trace plots are useful in assessing burn-in. If there are too many hyperparameters to plot them all, then it is most useful to visualize the log likelihood (e.g., plot(fit$ll, type = "l")).

Value

...N/A

bhetGP documentation built on Aug. 8, 2025, 6:34 p.m.