object {approximator}R Documentation

Optimization of posterior likelihood of hyperparameters

Description

Returns the likelihood of a set of hyperparameters given the data. Functions opt1() and opt.gt.1() find hyperparameters that maximize the relevant likelihood for level 1 and higher levels respectively.

Usage

object(level, D, z, basis, subsets, hpa)
opt.1(D, z, basis, subsets, hpa.start, give.answers=FALSE, ...)
opt.gt.1(level, D, z, basis, subsets, hpa.start, give.answers=FALSE, ...)

Arguments

level level
D Design matrix for top-level code
z Data
basis Basis function
subsets subsets object
hpa hyperparameter object
hpa.start Starting value for hyperparameter object
give.answers Boolean, with default FALSE meaning to return just the point estimate, and TRUE meaning to return extra information from the call to optim().
... Extra arguments passed to optim()

Details

This function is the object function used in toy optimizers optimal.hpa().

Author(s)

Robin K. S. Hankin

References

M. C. Kennedy and A. O'Hagan 2000. “Predicting the output from a complex computer code when fast approximations are available” Biometrika, 87(1): pp1-13

Examples

data(toyapps)
object(level=4, D=D1.toy , z=z.toy,basis=basis.toy,
   subsets=subsets.toy, hpa=hpa.fun.toy(1:19))
object(level=4, D=D1.toy , z=z.toy,basis=basis.toy,
   subsets=subsets.toy, hpa=hpa.fun.toy(3+(1:19)))

[Package approximator version 1.0-28 Index]