tmle.SL.dbarts2 {tmle} | R Documentation |
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 class 'tmle.SL.dbarts2'
predict(object, newdata, family, ...)
Y |
Dependent variable |
X |
Predictor covariate matrix or data frame used as training set |
newX |
Predictor covariate matrix or data frame for which predictions should be made |
family |
Regression family, 'gaussian' or 'binomial' |
obsWeights |
observation-level weights |
id |
identifier to group observations, not used |
sigest |
An estimate of error variance. See |
sigdf |
Degrees of freedom for error variance prior. See |
sigquant |
Quantile of error variance prior. See |
k |
Tuning parameter that controls smoothing. Larger values are more conservative, see |
power |
Power parameter for tree prior |
base |
Base parameter for tree prior |
binaryOffset |
Allows fits with probabilities shrunk towards values other than 0.5. See |
ntree |
Number of trees in the sum-of-trees formulation |
ndpost |
Number of posterior draws after burn in |
nskip |
Number of MCMC iterations treated as burn in |
printevery |
How often to print messages |
keepevery |
Every |
keeptrainfits |
If |
usequants |
Controls how tree decisions rules are determined. See |
numcut |
Maximum number of possible values used in decision rules |
printcutoffs |
Number of cutoff rules to print to screen. |
nthread |
Integer specifying how many threads to use |
keepcall |
Returns the call to BART when |
verbose |
Ignored for now |
... |
Additional arguments passed on to plot or control functions |
object |
Object of type tmle.SL.dbarts2 |
newdata |
Matrix or dataframe used to get predictions from the fitted model |
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.
an object of type tmle.SL.dbarts2 used internally by Super Learner
Chris Kennedy and Susan Gruber