oesg: Occurrence ETS general model

In smooth: Forecasting Using State Space Models

Occurrence ETS general model

Description

Wrapper of omg that fits a general occurrence (probability) model — two parallel ETS sub-models A and B combined via a Beta-distribution link — to a univariate intermittent time series. ARIMA components and regression formulas are disabled; use omg directly if those are needed.

Usage

oesg(y, modelA = "MNN", modelB = modelA, lags = c(frequency(y)),
  persistenceA = NULL, persistenceB = persistenceA, phiA = NULL,
  phiB = phiA, initial = c("backcasting", "optimal", "two-stage",
  "complete"), ic = c("AICc", "AIC", "BIC", "BICc"), h = 0,
  holdout = FALSE, bounds = c("usual", "admissible", "none"),
  etsA = c("conventional", "adam"), etsB = etsA, xregA = NULL,
  xregB = NULL, regressorsA = c("use", "select"),
  regressorsB = regressorsA, silent = TRUE, ...)

Arguments

y	Univariate numeric vector or time series. Non-binary input is binarised internally by omg.
modelA	Three-letter ETS specification for sub-model A.
modelB	Three-letter ETS specification for sub-model B. Defaults to modelA.
lags	Vector of seasonal lags. Defaults to frequency(y).
persistenceA	Optional persistence vector for sub-model A.
persistenceB	Optional persistence vector for sub-model B. Defaults to persistenceA.
phiA	Optional damping parameter for sub-model A.
phiB	Optional damping parameter for sub-model B. Defaults to phiA.
initial	Initialisation method passed to both sub-models.
ic	Information criterion for model selection.
h	Forecast horizon.
holdout	If TRUE, a holdout of size h is withheld.
bounds	Parameter bounds type.
etsA	ETS type for sub-model A: "conventional" or "adam".
etsB	ETS type for sub-model B. Defaults to etsA.
xregA	Optional numeric vector or matrix of exogenous regressors for sub-model A, aligned with y.
xregB	Optional numeric vector or matrix of exogenous regressors for sub-model B, aligned with y.
regressorsA	How to handle xregA: "use" or "select".
regressorsB	How to handle xregB. Defaults to regressorsA.
silent	If TRUE, suppresses output and plot.
...	Additional arguments forwarded to omg.

Value

An object of class c("omg","om","smooth","occurrence").

See Also

omg, oes

Examples

set.seed(42)
y <- rbinom(120, 1, 0.3)
m <- oesg(y, modelA="MNN", modelB="MNN")
forecast(m, h=12)

smooth documentation built on June 21, 2026, 9:06 a.m.