IMSL Statistics Reference Guide > Time Series and Forecasting
  

Time Series and Forecasting
 
This section contains the following topics:
*ARIMA Models
* ARMA Function (PV-WAVE Advantage)—Computes least-squares or method-of-moments estimates of parameters and optionally computes forecasts and their associated probability limits.
* MAX_ARMA Function (PV-WAVE Advantage)—Exact maximum likelihood estimation of the parameters in a univariate ARMA (autoregressive, moving average) time series model.
* AUTO_UNI_AR Function (PV-WAVE Advantage)—Automatic selection and fitting of a univariate autoregressive time series model.
* TS_OUTLIER_IDENTIFICATION Function (PV-WAVE Advantage)—Detects and determines outliers and simultaneously estimates the model parameters in a time series whose underlying outlier free series follows a general seasonal or nonseasonal ARMA model.
* TS_OUTLIER_FORECAST Function (PV-WAVE Advantage)—Computes forecasts, their associated probability limits and y weights for an outlier contaminated time series whose underlying outlier free series follows a general seasonal or nonseasonal ARMA model.
* AUTO_ARIMA Function (PV-WAVE Advantage)—Automatically identifies time series outliers, determines parameters of a multiplicative seasonal ARIMA model and produces forecasts that incorporate the effects of outliers whose effects persist beyond the end of the series.
* DIFFERENCE Function (PV-WAVE Advantage)—Performs differencing on a time series.
* SEASONAL_FIT Function (PV-WAVE Advantage)—Estimates the optimum seasonality parameters for a time series using an autoregressive model, AR(p), to represent the time series.
*Model Construction and Evaluation Utilities
* BOXCOXTRANS Function (PV-WAVE Advantage)—Perform a Box-Cox transformation.
* AUTOCORRELATION Function (PV-WAVE Advantage)—Sample autocorrelation function.
* CROSSCORRELATION Function (PV-WAVE Advantage)—Computes the sample cross-correlation function of two stationary time series.
* MULTI_CROSS Function (PV-WAVE Advantage)—Computes the multichannel cross-correlation function of two mutually stationary multichannel time series.
* PARTIAL_AC Function (PV-WAVE Advantage)—Sample partial autocorrelation function.
* LACK_OF_FIT Function (PV-WAVE Advantage)—Lack-of-fit test based on the corrleation function.
* ESTIMATE_MISSING Function (PV-WAVE Advantage)—Estimates missing values in a time series.
*GARCH Modeling
* GARCH Function (PV-WAVE Advantage)—Compute estimates of the parameters of a GARCH(p,q) model.
*Frequency Domain Modeling
* KALMAN Procedure (PV-WAVE Advantage)—Performs Kalman filtering and evaluates the likelihood function for the statespace model.

Version 2017.0
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