weighting: Marginal-Likelihood Weighting Used

In badp: Bayesian Averaging for Dynamic Panels

Marginal-Likelihood Weighting Used

Description

Returns the approximation to the marginal likelihood used to weight the models, and the learning rate it implies.

Usage

weighting(x, ...)

## S3 method for class 'badp_bma'
weighting(x, ...)

learning_rate(x, ...)

## S3 method for class 'badp_bma'
learning_rate(x, ...)

Arguments

x	An object of class badp_bma.
...	Arguments passed to methods.

Details

The four approximations are described in bma. Three of them share the same construction at different learning rates, so the rate is the quantity that distinguishes them; the fourth, "uip", alters the penalty instead and has no learning rate.

Value

For weighting, a character string. For learning_rate, a single number, or NA when the weighting does not correspond to a learning rate.

See Also

bma

Examples

data(full_model_space)
results <- bma(full_model_space)

weighting(results)
learning_rate(results)

badp documentation built on Sept. 15, 2026, 1:08 a.m.