expSmoot: Simple Exponential Smoothing Method

Description Usage Arguments Value Author(s) See Also Examples

View source: R/forecastFunctions.R

Description

Estimation of Simple Exponential Smoothing Method

Usage

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	expSmoot(y, h=5, ell0=NULL, alpha=NULL, lower = c(-1e+10, 0.1), 
	upper = c(1e+10, 0.99))

Arguments

y

Object of time series class.

h

Number of required forecasting periods.

ell0

The value of ell0^* parameter.

alpha

The value of alpha parameter.

lower

The lower limit of parametric space.

upper

The upper limit of parametric space.

Value

A list containing the elements:

$y

The original time series.

$par

The estimated values for (ell^*, alpha) parameters

$mean

The forecasting values

$fitted

A time series element with the fitted points.

$residuals

A time series element with the residual points.

Author(s)

Jose Augusto Fiorucci, Francisco Louzada and Bao Yiqi

See Also

forecTheta-package, stheta, dotm

Examples

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y1 = 2+ 0.15*(1:20) + rnorm(20,2)
y2 = y1[20]+ 0.3*(1:30) + rnorm(30,2)
y =  as.ts(c(y1,y2))

expSmoot(y, h=10)

forecTheta documentation built on May 29, 2017, 7:53 p.m.