Compute marginals using Bayesian Model Averaging

Description

fitmargBMA takes a list of marginal distributions and weights (presumably, based on some marginal likelihoods) and computes a final distribution by weighting.

fitmargBMA2 takes a list of INLA models and computes Bayesian Model Averaging on some of their components.

fitmatrixBMA performs averaging on a list of matrices.

fitlistBMA performs averaging of elements in lists.

Usage

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fitmargBMA(margs, ws, len = 100)
fitmargBMA2(models, ws, item)
fitmatrixBMA(models, ws, item)
fitlistBMA(models, ws, item)

Arguments

margs

List of 2-column matrices with the values of the (marginal) distributions.

models

List of INLA models to be averaged.

ws

Vector of weights. They do not need to sum up to one.

len

Length of the x-vector to compute the weighted distribution.

item

Name of the elements of an INLA object to be used in the Model Averaging.

Details

For fitmargBMA, distributions provided are averaging according to the weights provided. A new probability distribution is obtained.

fitmargBMA2 uses a list of INLA models to compute Model Averaging on some of their components (for example, the fitted values).

fitmatrixBMA performs averaging on a list of matrices.

fitlistBMA performs averaging of a list of a list of matrices.

Value

fitmargBMA returns a 2-column matrix with the weighted marginal distribution.

fitmargBMA2 returns a list of weighted components.

fitmatrixBMA returns a matrix.

fitlistBMA returns a list.

Author(s)

Virgilio G<f3>mez-Rubio <virgilio.gomez@uclm.es>