Time series analysis. Introduces several routines for handling/analyzing univariante time series. Includes ARMA, ARIMA and exponential smoothing routines.

As stated at NIST pages, time series is an ordered sequence of values of a variable at equally spaced time intervals. The usage of time series models is twofold:

• Obtain an understanding of the underlying forces and structure that produced the observed data.
• Fit a model and proceed to forecasting, monitoring or even feedback and feedforward control.

The fitting of time series models can be an ambitious undertaking. This unit utilizes the following:

• average smoothing,
• Holt-Winters single, double and triple exponential smoothing,
• ARMA and ARIMA models,
• ARAR model.

Literature used

1. Brockwell, P.J. and Davis, R.A. : Introduction to Time Series and Forecasting - second edition, Springer Verlag, New York, 2002.
2. Brockwell, P.J. and Davis, R.A. : Time Series: Theory and Methods - second edition, Springer Verlag, New York, 1991.
3. Shumway, R.H. and Stoffer, D.S. : Time Series Analysis and Its Applications, Springer Verlag, New York, 2000.
4. http://www.stat.unc.edu/faculty/hurd/progs/
5. http://www.itl.nist.gov/div898/handbook/pmc/section4/pmc43.htm
6. http://www.it.iitb.ac.in/~praj/acads/seminar/04329008_ExponentialSmoothing.pdf

Types

Name	Summary
TcfInitMethod	ARMA/ARIMA coefficients initial estimate method.

Routines

Name	Summary
ACF	Autocorrelation/autocovariance function.
ARARFit	Fit ARAR algorithm.
ARARForecast	Forecast time series by ARAR.
ARBurgFit	Burg AR estimation.
ARIMAForecast	Forecast using the ARIMA model.
ARIMASimulate	Simulate the ARIMA process.
ARMAAcf	Estimates autocorrelation/autocovariance function for the ARMA model.
ARMAForecast	Forecast time series by using ARMA(p,q) model.
ARMAHannahFit	Hannah-Rissanen ARMA estimation.
ARMAInnovationsFit	Innovations ARMA estimation.
ARMAKappa	ARMA process covariances.
ARMALogLike	-2log likelihood.
ARMAMLE	Estimate ARMA process AR and MA coefficients.
ARMAPredictors	ARMA model one-step ahead predictors.
ARMASimulate	Simulate the ARMA process.
ARYuleWalkerFit	Yule-Walker AR estimation.
AutoCov	Autocovariance function.
BoxCox	Box-Cox transformation.
BoxCoxInv	Inverse Box-Cox transformation.
BoxLjung	The box-Ljung statistics.
CheckARMACoeffs	Check AR(MA) coeefficients.
DoubleExpForecast	Double exponential forecast.
DoubleExpSmooth	Double exponential smoothing.
DurbinLevinson	The Durbin-Levinson algorithm.
Innovations	The innovations algorithm.
MovingAverage	Single moving average.
PACF	Partial autocorrelation function.
ShortenFilter	Memory-shortening filter.
SingleExpForecast	Single exponential forecast.
SingleExpSmooth	Single exponential smoothing.
TimeSeriesIntInit	Setup initial values for integrating ARMA series Setup initial values for integrating ARMA series.
TripleExpForecast	Triple exponential forecast.
TripleExpSmooth	Triple exponential smoothing.

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