ATA.Seasonality: Seasonality Tests for The ATAforecasting

In ATAforecasting: Automatic Time Series Analysis and Forecasting using the Ata Method

Seasonality Tests for The ATAforecasting

Description

This function is a class of seasonality tests using corrgram_test from ATAforecasting package, ndiffs and nsdiffs functions from forecast package. Also, this function is modified version of ndiffs and nsdiffs written by Hyndman et al. forecast package. Please review manual and vignette documents of latest forecast package. According to forecast package, ndiffs and nsdiffs functions to estimate the number of differences required to make a given time series stationary. ndiffs uses unit root tests to determine the number of differences required for time series to be made trend stationary. Several different tests are available:

• uroot.test = 'kpss' : the KPSS test is used with the null hypothesis that x has a stationary root against a unit-root alternative. Then the test returns the least number of differences required to pass the test at the level uroot.alpha.

• uroot.test = 'adf' : the Augmented Dickey-Fuller test is used.

• uroot.test = 'pp' : the Phillips-Perron test is used. In both of these cases, the null hypothesis is that x has a unit root against a stationary root alternative. Then the test returns the least number of differences required to fail the test at the level uroot.alpha.

nsdiffs uses seasonal unit root tests to determine the number of seasonal differences required for time series to be made stationary. Several different tests are available:

• suroot.test = 'seas' : a measure of seasonal strength is used, where differencing is selected if the seasonal strength (Wang, Smith & Hyndman, 2006) exceeds 0.64 (based on minimizing MASE when forecasting using auto.arima on M3 and M4 data).

• suroot.test = 'ch' : the Canova-Hansen (1995) test is used (with null hypothesis of deterministic seasonality)

• suroot.test = 'hegy' : the Hylleberg, Engle, Granger & Yoo (1990) test is used.

• suroot.test = 'ocsb' : the Osborn-Chui-Smith-Birchenhall (1988) test is used (with null hypothesis that a seasonal unit root exists).

• suroot.test = 'correlogram' : this function is written based on M4 Competition Seasonality Test.

Usage

ATA.Seasonality(input, ppy, attr_set)

Arguments

input	The data.
ppy	Frequency of the data.
attr_set	Assign from ATA.SeasAttr function. Attributes set for unit root, seasonality tests.

Value

TRUE if the serie has seasonality. Otherwise, FALSE.

Author(s)

Ali Sabri Taylan and Hanife Taylan Selamlar

References

#'\insertRefdickey1979ATAforecasting

#'\insertRefsaid1984ATAforecasting

#'\insertRefdhf1984ATAforecasting

#'\insertRefphillips1988ATAforecasting

#'\insertRefocsb1988ATAforecasting

#'\insertRefhegy1990ATAforecasting

#'\insertRefkpss1992ATAforecasting

#'\insertRefch1995ATAforecasting

#'\insertRefseas2006ATAforecasting

See Also

forecast, urca, tseries, uroot, stlplus, stR, stl, decompose, tbats, seasadj.

ATAforecasting documentation built on July 9, 2023, 7 p.m.