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bartMachine (version 1.3.4.1)

plot_y_vs_yhat: 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)

Value

None.

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.

Author

Adam Kapelner and Justin Bleich

See Also

bart_machine_get_posterior, calc_credible_intervals, calc_prediction_intervals

Examples

Run this code
if (FALSE) {
#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)
}

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