plot_y_vs_yhat: Plot the fitted Versus Actual Response

In bartMachine: Bayesian Additive Regression Trees

Plot the fitted Versus Actual Response

Description

Generates a plot actual versus fitted values and corresponding credible intervals or prediction intervals for the fitted values.

Usage

plot_y_vs_yhat(bart_machine, Xtest = NULL, ytest = NULL, 
credible_intervals = FALSE, prediction_intervals = FALSE, 
interval_confidence_level = 0.95)

Arguments

bart_machine	An object of class “bartMachine”.
Xtest	Optional argument for test data. If included, BART computes fitted values at the rows of Xtest. Else, the fitted values from the training data are used.
ytest	Optional argument for test data. Vector of observed values corresponding to the rows of Xtest to be plotted against the predictions for the rows of Xtest.
credible_intervals	If TRUE, Bayesian credible intervals are computed using the quantiles of the posterior distribution of \hat{f}(x). See calc_credible_intervals for details.
prediction_intervals	If TRUE, Bayesian predictive intervals are computed using the a draw of from \hat{f}(x). See calc_prediction_intervals for details.
interval_confidence_level	Desired level of confidence for credible or prediction intervals.

Value

None.

Note

This function is parallelized by the number of cores set in set_bart_machine_num_cores.

Author(s)

Adam Kapelner and Justin Bleich

See Also

bart_machine_get_posterior, calc_credible_intervals, calc_prediction_intervals

Examples

## Not run: 
#generate linear data
set.seed(11)
n  = 500 
p = 3
X = data.frame(matrix(runif(n * p), ncol = p))
y = 3*X[ ,1] + 2*X[ ,2] +X[ ,3] + rnorm(n)

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

##generate plot
plot_y_vs_yhat(bart_machine)

#generate plot with prediction bands
plot_y_vs_yhat(bart_machine, prediction_intervals = TRUE)

## End(Not run)

bartMachine documentation built on July 9, 2023, 5:59 p.m.