Description Usage Arguments Details Value Author(s) See Also Examples

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 vecotr of model indicators

1 | ```
tr.power.prior(kappa=2.0, trunc)
``` |

`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. |

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 distribution on the number of included predictos 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 hyerparameters.

Merlise Clyde

1 2 3 4 5 6 7 | ```
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 documentation built on May 19, 2017, 9:36 p.m.

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