rf_forecast: function to calculate point forecast, 95% confidence...

In seer: Feature-Based Forecast Model Selection

function to calculate point forecast, 95% confidence intervals, forecast-accuracy for new series

Description

Given the prediction results of random forest calculate point forecast, 95% confidence intervals, forecast-accuracy for the test set

Usage

rf_forecast(
  predictions,
  tslist,
  database,
  function_name,
  h,
  accuracy,
  holdout = TRUE
)

Arguments

predictions	prediction results obtained from random forest classifier
tslist	list of new time series
database	whethe the time series is from mcom or other
function_name	specify the name of the accuracy function (for eg., cal_MASE, etc.) to calculate accuracy measure, ( if a user written function the arguments for the accuracy function should be training period, test period and forecast).
h	length of the forecast horizon
accuracy	if true a accuaracy measure will be calculated
holdout	if holdout=TRUE take a holdout sample from your data to caldulate forecast accuracy measure, if FALSE all of the data will be used for forecasting. Default is TRUE

Value

a list containing, point forecast, confidence interval, accuracy measure

Author(s)

Thiyanga Talagala

seer documentation built on Oct. 1, 2022, 9:06 a.m.