predict.qreg_lightgbm: Predict method for Multiple Quantile Regression from lightgbm...

In jbrowell/ProbCast: Flexible Probabilistic Forecasting

Predict method for Multiple Quantile Regression from lightgbm Gradient Boosted Decision Trees.

Description

This function returns multiple quantile predictions as an object of class MultiQR based on a ProbCast gbm fitted model. S3 Method for for qreg_lightgbm objects

Usage

## S3 method for class 'qreg_lightgbm'
predict(
  object,
  newdata = NULL,
  quantiles = NULL,
  model_name = NULL,
  sort = T,
  sort_limits = NULL,
  ...
)

Arguments

object	fitted model of class qreg_lightgbm obtained from the function qreg_lightgbm().
newdata	data.frame of observations for which to make predictions
quantiles	the quantiles to predict. Default is all the quantiles present in object
model_name	the name of the model to be used for prediction. Unless specified, object$default_model is used.
sort	sort quantiles using SortQuantiles()?
sort_limits	Limits argument to be passed to SortQuantiles(). Constrains quantiles to upper and lower limits given by list(U=upperlim,L=lowerlim).
...	additional arguments; not currently used.

Details

this function returns predictive quantiles for each row in newdata, the result is returned as a MultiQR object

Value

Quantile forecasts in a MultiQR object.

Author(s)

Gordon McFadzean, [e-mail]

jbrowell/ProbCast documentation built on July 20, 2024, 1:53 p.m.