evalZdensity

the configuration of a single <code>GlmBayesMfp</code> model. The
null model is not allowed. It is interpreted in the context of
<code>object</code>.

config

the <code><a rd-options="" href="/link/GlmBayesMfp?package=glmBfp&version=0.0-51" data-mini-rdoc="glmBfp::GlmBayesMfp">GlmBayesMfp</a></code> object

object

zValues

return the approximate *conditional* density f(y | z)?
(not default)

conditional

print debugging information? (not default)

debug

should a higher-order correction of the
Laplace approximation be used? (not default)

higherOrderCorrection

Based on the result list from <code><a rd-options="" href="/link/glmBayesMfp?package=glmBfp&version=0.0-51" data-mini-rdoc="glmBfp::glmBayesMfp">glmBayesMfp</a></code>, for the first model
in the list, the marginal z density can be evaluated.

internal

Implements the Bayesian paradigm
for fractional polynomials in generalized linear
models, described by Held, Gravestock, Sabanes Bove (2015) <doi:10.1214/14-STS510>.
See package 'bfp' for the treatment of normal
models.

Isaac Gravestock

glmBfp

Bayesian Fractional Polynomials for GLMs

Daniel Sabanes Bove

David Maisonave

Terry Therneau

R Core Team 

evalZdensity function

the <code><a rd-options='' href='GlmBayesMfp'>GlmBayesMfp</a></code> object

Based on the result list from <code><a rd-options='' href='glmBayesMfp'>glmBayesMfp</a></code>, for the first model
in the list, the marginal z density can be evaluated.

evalZdensity: Evaluate the (negative log) unnormalized marginal z density in a given model.

Description

Usage

Arguments

Value