plot.coef.bma: Plots the posterior distributions of coefficients derived from Bayesian model averaging

Description

Displays plots of the posterior distributions of the coefficients generated by Bayesian model averaging over linear regression.

Usage

## S3 method for class 'coef.bma':
plot(x, e = 1e-04,  subset = 1:x$n.vars, ask=TRUE,...)

Arguments

object of class coeffients.bma

optional numeric value specifying the range over which the distributions are to be graphed.

subset

optional numerical vector specifying which variables to graph (including the intercept)

ask

Prompt for next plot

...

other parameters to be passed to plot and lines

Details

Produces plots of the posterior distributions of the coefficients under model averaging. The posterior probability that the coefficient is zero is represented by a solid line at zero, with height equal to the probability. The nonzero part of the distribution is scaled so that the maximum height is equal to the probability that the coefficient is nonzero. The parameter e specifies the range over which the distributions are to be graphed by specifying the tail probabilities that dictate the range to plot over.

References

Hoeting, J.A., Raftery, A.E. and Madigan, D. (1996). A method for simultaneous variable selection and outlier identification in linear regression. Computational Statistics and Data Analysis, 22, 251-270.

Examples

Run this code

library(MASS)
data(UScrime)
UScrime[,-2] = log(UScrime[,-2])
crime.bic = bas.lm(y ~ ., data=UScrime, n.models=2^15, prior="BIC")
plot(coefficients(crime.bic), ask=TRUE)