fitmarg: Fit posterior marginal distributions to points

In INLABMA: Bayesian Model Averaging with INLA

Fit posterior marginal distributions to points

Description

Compute (and re-scale, if necessary) the marginal from a set of points x and values of log-likelihood logy and log-prior density logp.

Usage

fitmarg(x, logy, logp = 0, usenormal = FALSE)

Arguments

x	Values of the random variable.
logy	Log-likelihood.
logp	Log-prior density.
usenormal	Whether use a Normal distribution for the fitted marginal.

Details

Fits a marginal at a set of points x from their log-likelihood and log-prior. The fitted marginal is re-scaled to integrate one if necessary. If usenormal=TRUE then the fitted marginal is supposed to be Normal, which is computed using the posterior mean and standard deviation of x.

Value

A function with the fitted marginal is returned.

Author(s)

Virgilio Gómez-Rubio <[e-mail]>

See Also

fitmargBMA, fitmargBMA2,mysplinefun

INLABMA documentation built on Nov. 18, 2023, 5:13 p.m.