tr.beta.binomial {BAS} | R Documentation |
Creates an object representing the prior distribution on models for BAS using a truncated Beta-Binomial Distribution on the Model Size
tr.beta.binomial(alpha = 1, beta = 1, trunc)
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. |
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.
returns an object of class "prior", with the family and hyperparameters.
Merlise Clyde
Other priors modelpriors: Bernoulli.heredity
,
Bernoulli
, beta.binomial
,
tr.poisson
, tr.power.prior
,
uniform
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" )