doit_approx: DoIt approximation of the target density

In sieste/doit: Bayesian Computation using Design of Experiments-Based Interpolation Technique

Description

Evaluate mean and variance of the DoIt approximation of the target density at a number of evaluation points.

Usage

doit_approx(doit, theta_eval)

Arguments

doit	An object of class 'doit', see function 'doit_fit'.
theta_eval	A data frame of evaluation points.

Value

A data frame of the provided evaluation points and the corresponding mean and variance of the DoIt approximation.

Examples

design = data.frame(x=rnorm(10), y=rnorm(10))
design$f = with(design, exp(-0.5*(x+y)^2))
fit = doit_fit(design)
theta_eval = expand.grid(x=seq(-2,2,.1), y=seq(-2,2,.1))
approx = doit_approx(fit, theta_eval)

sieste/doit documentation built on May 9, 2019, 4:10 p.m.