BAS: tr.power.prior – R documentation

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tr.power.prior

Truncated Power Prior Distribution for Models

Description

Creates an object representing the prior distribution on models for BAS using a truncated Distribution on the Model Size where the probability of gamma = p^-kappa |gamma| where gamma is the vector of model indicators

Usage

tr.power.prior(kappa = 2, trunc)

Arguments

`kappa`	parameter in the prior distribution that controls sparsity
`trunc`	parameter that determines truncation in the distribution i.e. P(gamma; alpha, beta, trunc) = 0 if \|gamma\| > trunc.

Details

The beta-binomial distribution on model size is obtained by assigning each variable inclusion indicator independent Bernoulli distributions with probability w, and then giving w a beta(alpha,beta) distribution. Marginalizing over w leads to the number of included predictors having a beta-binomial distribution. The default hyperparameters lead to a uniform distribution over model size. The Truncated version assigns zero probability to all models of size > trunc.

Value

returns an object of class "prior", with the family and hyperparameters.

Author(s)

Merlise Clyde

Examples

tr.power.prior(2, 8)
library(MASS)
data(UScrime)
UScrime[, -2] <- log(UScrime[, -2])
crime.bic <- bas.lm(y ~ .,
  data = UScrime, n.models = 2^15, prior = "BIC",
  modelprior = tr.power.prior(2, 8),
  initprobs = "eplogp"
)

BAS

Bayesian Variable Selection and Model Averaging using Bayesian Adaptive Sampling

v1.5.5

GPL (>= 3)

Authors

Merlise Clyde [aut, cre, cph] (ORCID=0000-0002-3595-1872), Michael Littman [ctb], Quanli Wang [ctb], Joyee Ghosh [ctb], Yingbo Li [ctb], Don van de Bergh [ctb]

Initial release

2020-1-24