Time Series Analysis Package
Functional Summary
Table 16.1 summarizes the functions in the TSA package.
Table 16.1: Functions in Time Series Analysis Package
TSA Function | Description |
|---|---|
Accumulates a univariate time series to a particular frequency | |
Accumulates a high-frequency time series to a lower frequency and expands the lower-frequency series to have the same length as the high-frequency series | |
Computes autocorrelation and autocovariance for a time series array | |
Performs tests to tentatively identify the autoregressive and moving average orders of mixed autoregressive moving average models | |
Computes the cross-correlation and cross-covariance for two time series arrays | |
Performs count distribution analysis for time series | |
Performs frequency analysis of a time series | |
Tests for intermittency of a univariate time series | |
Computes the inverse autocorrelation for a time series array | |
Computes statistics for a set of values within a moving time window | |
Computes the partial autocorrelation for a time series array | |
Scales a time series between the minimum value and the maximum value of the original time series | |
Computes the seasonal indices of a univariate time series using classical decomposition | |
Computes the seasonal indices of a univariate time series by using regression seasonal dummies | |
Tests for seasonality of a univariate time series | |
Performs similarity analysis for time series | |
Tests for stationarity of a univariate time series | |
Transforms time series according to the specified transformation type | |
Tests whether a univariate time series is unbiased | |
Tests for white noise of a time series array |