Development repository for the tsintermittent package for R. Stable version can be found at: https://cran.r-project.org/web/packages/tsintermittent/index.html
Functions and wrappers for producing intermittent demand forecasts
for R, including Croston’s method and its variants, TSB, iMAPA,
classification of intermittent series, and empirical quantiles of the
demand over the lead time. The parameters and initial values of all
methods can be optimised using cost functions designed for intermittent
demand. See vignette("tsintermittent") for an
introduction.
To install the development version from GitHub use:
if (!require(“remotes”)){install.packages(“remotes”)}
remotes::install_github(“trnnick/tsintermittent”, build_vignettes=TRUE)
crost(): Croston’s method, SBA, and SBJ.crost.ma(): Croston-style moving averages.tsb(): TSB method.sexsm(): Simple exponential smoothing.imapa(): iMAPA, combining forecasts from multiple
temporal aggregation levels.data.frc(): Forecasting multiple series with a single
call.probs of the forecasting methods: quantiles
of the demand over the lead time and safety stock, when fitting a
model.lt.dist(): Quantiles of the demand over the lead time,
for a fitted model with any lead time and probabilities, or for
forecasts produced otherwise.print(), summary(), coef(),
and fitted().plot(): per-period and lead time views of the
forecasts, plus additional views for iMAPA.forecast(): point forecasts for any horizon, optionally
for new data.model of the forecasting methods, or
model.fit of imapa(): a fitted model applied
to new data without optimisation.idclass(): Classification of intermittent demand
series, to select between Croston’s method, SBA, and SES.print() and plot() of the
classification.crost.decomp(): Croston decomposition into non-zero
demand and intervals.simID(): Simulation of intermittent demand series.ts.data1 and ts.data2: Example
series.Happy forecasting!