Plot the fitted Versus Actual Response

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,
  verbose = TRUE
)

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.
verbose: If TRUE, prints plots to the active device.

Value

None.

Note

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

Author

Adam Kapelner and Justin Bleich

Examples

if (FALSE) { # \dontrun{
#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)
} # }