sda.bias.correction — debias.ML • PEcAnAssimSequential

This function helps to correct the forecasts' biases based on ML (random forest) training on the previous time points.

Usage

debias.ML(pred.name, cov.names, dat.train, dat.pred, var.name, py.init)

pred.name: character: the name for the predictive variable.
cov.names: character: the name for the covariates.
dat.train: data.frame: data frame containing associated covariates and predictive variable for ML training.
dat.pred: data.frame: data frame containing associated covariates for prediction.
var.name: character: variable name to be predicted.
py.init: R function: R function to initialize the python functions. Default is NULL. the default random forest will be used if `py.init` is NULL.

list: the ML predicted residuals and other ML outputs.

Dongchen Zhang