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SuperLearner wrapper for Multivariate Adaptive Regression Splines

SL.earth.gamma.log.Rd

A SuperLearner wrapper that implements Multivariate Adaptive Regression Splines using the Gamma family with a log link.

Usage

SL.earth.gamma.log(
  Y,
  X,
  newX,
  degree = 2,
  penalty = 3,
  nk = max(21, 2 * ncol(X) + 1),
  pmethod = "backward",
  nfold = 0,
  ncross = 1,
  minspan = 0,
  endspan = 0,
  ...
)

Arguments

Y

A numeric vector of outcome values.

X

A numeric matrix or data.frame of covariates and treatment.

newX

A numeric matrix or data.frame of predictors.

degree

Maximum degree of interaction. Default is 3, meaning build a model with interaction terms.

penalty

Generalized Cross Validation (GCV) penalty per knot. Defaults is 3.

nk

Maximum number of model terms before pruning, i.e., the maximum number of terms created by the forward pass. Includes the intercept. The default is semi-automatically calculated from the number of predictors but may need adjusting.

pmethod

Pruning method. One of: "backward", "none", "exhaustive", "forward", "seqrep", "cv". Default is "backward". Specify pmethod="cv" to use cross-validation to select the number of terms. This selects the number of terms that gives the maximum mean out-of-fold RSq on the fold models. Requires the nfold argument. Use "none" to retain all the terms created by the forward pass.

nfold

Number of cross-validation folds. Default is 0, no cross validation.

ncross

Only applies if nfold>1. Number of cross-validations. Each cross-validation has nfold folds. Default 1.

minspan

Minimum number of observations between knots. (This increases resistance to runs of correlated noise in the input data.) The default minspan=0 is treated specially and means calculate the minspan internally, as per Friedman's MARS paper section 3.8 with alpha = 0.05.

endspan

Minimum number of observations before the first and after the final knot. The default endspan=0 is treated specially and means calculate the endspan internally, as per the MARS paper equation 45 with alpha = 0.05.

...

Any additional arguments.

Value

A list with components:

  • pred: A numeric vector of predictions on newX.

  • fit: A list containing the fitted model object.

Details

A copy of [SuperLearner::SL.earth]() but using the Gammma family, which is itself a wrapper of [earth::earth](). See [earth::earth]() for more details.