spooky: Spectral forecasting with jackknife resampling

In spooky: Time Feature Extrapolation Using Spectral Analysis and Jack-Knife Resampling

Spectral forecasting with jackknife resampling

Description

Automatic jack-knife of spectral analysis for time feature extrapolation

Usage

spooky(
  df,
  seq_len = NULL,
  lno = NULL,
  n_samp = 30,
  n_windows = 3,
  ci = 0.8,
  smoother = FALSE,
  dates = NULL,
  error_scale = "naive",
  error_benchmark = "naive",
  seed = 42
)

Arguments

df	Numeric or categorical time-feature data frame.
seq_len	Forecast horizon or range of horizons to search.
lno	Jackknife leave-out value or search range.
n_samp	Number of candidate configurations.
n_windows	Number of validation windows.
ci	Confidence level for prediction summaries.
smoother	Apply a moving-average smoother to numeric data.
dates	Optional Date vector matching 'df'.
error_scale	Scale used by numeric error metrics.
error_benchmark	Benchmark used by relative error metrics.
seed	Random seed.

Value

An object of class 'spooky_fit'.

Author(s)

Maintainer: Giancarlo Vercellino [e-mail]

spooky documentation built on Sept. 7, 2026, 9:07 a.m.