bart in the dbarts packageThese functions are used internally, not typically called by the user
tmle.SL.dbarts2(Y, X, newX, family, obsWeights, id, sigest = NA, sigdf = 3,
sigquant = 0.90, k = 2, power = 2.0, base = 0.95, binaryOffset = 0.0,
ntree = 200, ndpost = 1000, nskip = 100, printevery = 100, keepevery = 1,
keeptrainfits = TRUE, usequants = FALSE, numcut = 100,printcutoffs = 0,
nthread = 1, keepcall = TRUE,verbose = FALSE, ...)
tmle.SL.dbarts.k.5(Y, X, newX, family, obsWeights, id, sigest = NA, sigdf = 3,
sigquant = 0.90, k = 0.5, power = 2.0, base = 0.95, binaryOffset = 0.0,
ntree = 200, ndpost = 1000, nskip = 100, printevery = 100, keepevery = 1,
keeptrainfits = TRUE, usequants = FALSE, numcut = 100,printcutoffs = 0,
nthread = 1, keepcall = TRUE,verbose = FALSE, ...)
# S3 method for tmle.SL.dbarts2
predict(object, newdata, family, ...)an object of type tmle.SL.dbarts2 used internally by Super Learner
Dependent variable
Predictor covariate matrix or data frame used as training set
Predictor covariate matrix or data frame for which predictions should be made
Regression family, 'gaussian' or 'binomial'
observation-level weights
identifier to group observations, not used
An estimate of error variance. See bart documentation
Degrees of freedom for error variance prior. See bart documentation
Quantile of error variance prior. See bart documentation
Tuning parameter that controls smoothing. Larger values are more conservative, see Details
Power parameter for tree prior
Base parameter for tree prior
Allows fits with probabilities shrunk towards values other than 0.5. See bart documentation
Number of trees in the sum-of-trees formulation
Number of posterior draws after burn in
Number of MCMC iterations treated as burn in
How often to print messages
Every keepevery draw is kept to be returned to the user
If TRUE the draws of \(f(x)\) for \(x\) corresponding to the rows of x.train are returned
Controls how tree decisions rules are determined. See bart documentation
Maximum number of possible values used in decision rules
Number of cutoff rules to print to screen. \(0\) prints nothing
Integer specifying how many threads to use
Returns the call to BART when TRUE
Ignored for now
Additional arguments passed on to plot or control functions
Object of type tmle.SL.dbarts2
Matrix or dataframe used to get predictions from the fitted model
Chris Kennedy and Susan Gruber
tmle.SL.dbarts2 is in the default library for estimating \(Q\). It uses the default setting in the dbarts package, \(k=2\). tmle.SL.dbarts.k.5 is used to estimate the components of \(g\). It sets \(k=0.5\), to avoid shrinking predicted values too far from \((0,1)\). See bart documentation for more information.
SuperLearner