FcAutoARIMA: Forcasting with Automatic ARIMA

In Mthrun/TSAT: Time Series Analysis Tools (TSAT)

Forcasting with Automatic ARIMA

Description

Automatic autoregressive and moving average modelling with difference filter

Usage

FcAutoARIMA(DataVec, SplitAt, ForecastHorizon, Time, PlotIt = TRUE,


                 Seasonal=TRUE,PlotBackwardInd, main = "", xlab = "Time", ylab =
                 
                 
                 "Data", ...)

Arguments

DataVec	[1:n] numerical vector of regular (equidistant) time series data.
SplitAt	Integer, splits data in test and train at this index. If not given n is used
ForecastHorizon	Number of Forecast units of time
Time	[1:n] character vector of Time in the length of data
PlotIt	Optional, if TRUE: Plots result
Seasonal	Optional, if FALSE: no seasonality in data an one step forecast only
PlotBackwardInd	Optional, how many units to plot back in time?
main	see plot
xlab	see plot
ylab	see plot
...	further arguments passed on to see plot

Details

- Autoregressive part (AR) with Lag 4 w.r.t signal term

- Difference Filter (I): 1 Lag, because noon stationary TS (time dependent expectation value of time series)

- Moving Average (MA) with Lag 4 w.r.t noise term

- requires homoscedastic time series - variance does not depend on time

If n-SplitAt=ForecastHorizon then forecast is completely on test data.

If ForecastHorizon>n-SplitAt then a real forecast is made of ForecastHorizon-(n-SplitAt) steps.

If SplitAt=n then the complete data set is used in estimating the forecast.

Value

List of

Forecast	[1:ForecastHorizon] of test data Y, test time and forecast FF
ArimaObject	Forecast object, the output of forecast
Model	Model, the output of auto.arima

in mode invisible

Note

wrapper for auto.arima

Author(s)

Michael Thrun

References

Hyndman, RJ and Khandakar, Y (2008) "Automatic time series forecasting: The forecast package for R", Journal of Statistical Software, 26(3).

Wang, X, Smith, KA, Hyndman, RJ (2006) "Characteristic-based clustering for time series data", Data Mining and Knowledge Discovery, 13(3), 335-364.

See Also

auto.arima

Examples

data("TempMelbourneAustralia")
res = FcAutoARIMA(TempMelbourneAustralia$Temp, SplitAt = length(TempMelbourneAustralia$Temp)-250,ForecastHorizon = 250, Time=TempMelbourneAustralia$Time)

Mthrun/TSAT documentation built on Feb. 5, 2024, 11:15 p.m.