| tr.beta.binomial {BAS} | R Documentation |
Truncated Beta-Binomial Prior Distribution for Models
Description
Creates an object representing the prior distribution on models for BAS using a truncated Beta-Binomial Distribution on the Model Size
Usage
tr.beta.binomial(alpha = 1, beta = 1, trunc)
Arguments
alpha |
parameter in the beta prior distribution |
beta |
parameter in the beta prior distribution |
trunc |
parameter that determines truncation in the distribution i.e. P(M; alpha, beta, trunc) = 0 if M > 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
See Also
Other priors modelpriors:
Bernoulli.heredity(),
Bernoulli(),
beta.binomial(),
tr.poisson(),
tr.power.prior(),
uniform()
Examples
tr.beta.binomial(1, 10, 5)
library(MASS)
data(UScrime)
UScrime[, -2] <- log(UScrime[, -2])
crime.bic <- bas.lm(y ~ .,
data = UScrime, n.models = 2^15, prior = "BIC",
modelprior = tr.beta.binomial(1, 1, 8),
initprobs = "eplogp"
)