bartMachine (version 1.2.6)

calc_credible_intervals: Calculate Credible Intervals

Description

Generates credible intervals for \(\hat{f}(x)\) for a specified set of observations.

Usage

calc_credible_intervals(bart_machine, new_data, 
ci_conf = 0.95)

Value

Returns a matrix of the lower and upper bounds of the credible intervals for each observation in new_data.

Arguments

bart_machine

An object of class ``bartMachine''.

new_data

A data frame containing observations at which credible intervals for \(\hat{f}(x)\) are to be computed.

ci_conf

Confidence level for the credible intervals. The default is 95%.

Author

Adam Kapelner and Justin Bleich

Details

This interval is the appropriate quantiles based on the confidence level, ci_conf, of the predictions for each of the Gibbs samples post-burn in.

See Also

calc_prediction_intervals, bart_machine_get_posterior

Examples

#generate Friedman data
set.seed(11)
n  = 200 
p = 5
X = data.frame(matrix(runif(n * p), ncol = p))
y = 10 * sin(pi* X[ ,1] * X[,2]) +20 * (X[,3] -.5)^2 + 10 * X[ ,4] + 5 * X[,5] + rnorm(n)

##build BART regression model
bart_machine = bartMachine(X, y)

#get credible interval
cred_int = calc_credible_intervals(bart_machine, X)
print(head(cred_int))