regressionFunction.Forest: Forest Regression
In rizbicki/FlexCoDE: Fits Flexible Conditional Estimator via Regression

This function is typically not directly used by the user; it is used inside fitFlexCoDE

1	regressionFunction.Forest(x, responses, extra = NULL)

`x`	matrix with covariates that will be used for training
`responses`	matrix where each column is a response for the training data
`extra`	list with one components named p0Vec, which contains a vetor with different number of variables randomly sampled as candidates at each split of the forest regression (aka mtry in randomForest package); the function will choose the best value among them; one component named ntree which contains the number of tree to be used by the forest (default is 500), and one component named maxnodes which contains the number of f terminal nodes trees in the forest can have (if not given, trees are grown to the maximum possible). The list can also contain a component named nCores which contains the number of cores to be used for parallel computing. Default is one.