confint.pred: Compute Credible (Bayesian Confidence) Intervals for a BAS...

In BAS: Bayesian Variable Selection and Model Averaging using Bayesian Adaptive Sampling

Compute Credible (Bayesian Confidence) Intervals for a BAS predict object

Description

Compute credible intervals for in-sample or out of sample prediction or for the regression function

Usage

## S3 method for class 'pred.bas'
confint(object, parm, level = 0.95, nsim = 10000, ...)

Arguments

object	an object created by predict.bas
parm	character variable, "mean" or "pred". If missing parm='pred'.
level	the nominal level of the (point-wise) credible interval
nsim	number of Monte Carlo simulations for sampling methods with BMA
...	optional arguments to pass on to next function call; none at this time.

Details

This constructs approximate 95 percent Highest Posterior Density intervals for 'pred.bas' objects. If the estimator is based on model selection, the intervals use a Student t distribution using the estimate of g. If the estimator is based on BMA, then nsim draws from the mixture of Student t distributions are obtained with the HPD interval obtained from the Monte Carlo draws.

Value

a matrix with lower and upper level * 100 percent credible intervals for either the mean of the regression function or predicted values.

Author(s)

Merlise A Clyde

See Also

predict.bas

Other bas methods: BAS, bas.lm(), coef.bas(), confint.coef.bas(), diagnostics(), fitted.bas(), force.heredity.bas(), image.bas(), plot.confint.bas(), predict.bas(), predict.basglm(), summary.bas(), update.bas(), variable.names.pred.bas()

Other CI methods: confint.coef.bas(), plot.confint.bas()

Examples

data("Hald")
hald.gprior =  bas.lm(Y~ ., data=Hald, alpha=13, prior="g-prior")
hald.pred = predict(hald.gprior, estimator="BPM", predict=FALSE, se.fit=TRUE)
confint(hald.pred, parm="mean")
confint(hald.pred)  #default
hald.pred = predict(hald.gprior, estimator="BMA", predict=FALSE, se.fit=TRUE)
confint(hald.pred)

BAS documentation built on Sept. 30, 2024, 9:19 a.m.