Prediction for boosted functional regression model

Description

Takes a fitted FDboost-object produced by FDboost() and produces predictions given a new set of values for the model covariates or the original values used for the model fit. This is a wrapper function for predict.mboost()

Usage

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## S3 method for class 'FDboost'
predict(object, newdata = NULL, which = NULL,
  toFDboost = TRUE, ...)

Arguments

object

a fitted FDboost-object

newdata

a named list or a data frame containing the values of the model covariates at which predictions are required. If this is not provided then predictions corresponding to the original data are returned. If newdata is provided then it should contain all the variables needed for prediction, in the format supplied to FDboost, i.e., functional predictors must be supplied as matrices with each row corresponding to one observed function.

which

a subset of base-learners to take into account for computing predictions or coefficients. If which is given (as an integer vector corresponding to base-learners) a list is returned.

toFDboost

logical, defaults to TRUE. In case of regular response in wide format (i.e. response is supplied as matrix): should the predictions be returned as matrix, or list of matrices instead of vectors

...

additional arguments passed on to predict.mboost().

Value

a matrix or list of predictions depending on values of unlist and which

See Also

FDboost for the model fit and plotPredicted for a plot of the observed values and their predictions.

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