ARIMA Models

ARMA Function—Computes least-squares or method-of-moments estimates of parameters and optionally computes forecasts and their associated probability limits.

MAX_ARMA Function—Exact maximum likelihood estimation of the parameters in a univariate ARMA (autoregressive, moving average) time series model.

AUTO_UNI_AR Function—Automatic selection and fitting of a univariate autoregressive time series model.

TS_OUTLIER_IDENTIFICATION Function—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—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—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—Performs differencing on a time series.

SEASONAL_FIT Function—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—Perform a Box-Cox transformation.

AUTOCORRELATION Function—Sample autocorrelation function.

CROSSCORRELATION Function—Computes the sample cross-correlation function of two stationary time series.

MULTI_CROSS Function—Computes the multichannel cross-correlation function of two mutually stationary multichannel time series.

PARTIAL_AC Function—Sample partial autocorrelation function.

LACK_OF_FIT Function—Lack-of-fit test based on the corrleation function.

ESTIMATE_MISSING Function—Estimates missing values in a time series.

GARCH Modeling

GARCH Function—Compute estimates of the parameters of a GARCH(p,q) model.

Frequency Domain Modeling

KALMAN Procedure—Performs Kalman filtering and evaluates the likelihood function for the statespace model.