blockBootstrap: Futures through single season block bootstrapping

In smimodel: Sparse Multiple Index Models for Nonparametric Forecasting

Futures through single season block bootstrapping

Description

Generates possible future sample paths by applying the single season block bootstrap method.

Usage

blockBootstrap(
  object,
  newdata,
  resids,
  preds,
  season.period = 1,
  m = 1,
  num.futures = 1000,
  exclude.trunc = NULL,
  recursive = FALSE,
  recursive_colRange = NULL
)

Arguments

object	Fitted model object.
newdata	Test data set. Must be a data set of class tsibble.
resids	In-sample residuals from the fitted model.
preds	Predictions for the test set (i.e. data for the forecast horizon).
season.period	Length of the seasonal period.
m	Multiplier. (Block size = season.period * m)
num.futures	Number of possible future sample paths to be generated.
exclude.trunc	The names of the predictor variables that should not be truncated for stable predictions as a character string.
recursive	Whether to obtain recursive forecasts or not (default - FALSE).
recursive_colRange	If recursive = TRUE, The range of column numbers in test data to be filled with forecasts.

Value

A matrix of simulated future sample paths.

smimodel documentation built on April 8, 2026, 5:06 p.m.