p.page4 {calibrator}R Documentation

A postiori probability of hyperparameters

Description

Function to determine a postiori probability of hyperparameters rho, lambda and psi2, given observations and psi1.

Usage

p.page4(D1, D2, H1, H2, V, y, z, E.theta, Edash.theta, extractor, include.prior=FALSE,
lognormally.distributed=FALSE, return.log=FALSE, phi)

Arguments

D1 Matrix of code run points
D2 Matrix of observation points
H1 Basis function (vectorized)
H2 Regression function for D2
V Covariance matrix; default value of NULL results in the function evaluating it (but this takes a long time, so supply V if known)
y Vector of code outputs
z Vector of observation values
E.theta Expectation over theta
Edash.theta Expectation over theta WRT E'
extractor Function to extract independent variables and parameters from D1
include.prior Boolean, with TRUE meaning to include the prior PDF for theta and default value of FALSE meaning to return the likelihood multiplied by an undetermined constant
lognormally.distributed Boolean with TRUE meaning to assume lognormality. See prob.psi1 for details
return.log Boolean, with default FALSE meaning to return the probability, and TRUE meaning to return the (natural) logarithm of the probability (which is useful when considering very small probabilities)
phi Hyperparameters

Author(s)

Robin K. S. Hankin

References

See Also

W2

Examples

data(toys)

p.page4(D1=D1.toy, D2=D2.toy, H1=H1.toy, H2=H2.toy, V=NULL, y=y.toy,
z=z.toy,E.theta=E.theta.toy, Edash.theta=Edash.theta.toy, extractor=extractor.toy, phi=phi.toy)

## Now compare the above value with p.page4() calculated with phi
## differing only in psi2:

phi.toy.new <- phi.change(phi.fun=phi.fun.toy, old.phi = phi.toy, psi2=c(8,8,8))

p.page4(D1=D1.toy, D2=D2.toy, H1=H1.toy, H2=H2.toy, V=V.toy, y=y.toy, z=z.toy,
E.theta=E.theta.toy, Edash.theta=Edash.theta.toy,
extractor=extractor.toy, phi=phi.toy.new)
## different!


[Package calibrator version 1.0-58 Index]