| combined_test {seastests} | R Documentation |
Ollech and Webel's combined seasonality test
Description
Ollech-Webel overall seasonality test that combines results from different seasonality tests.
Usage
combined_test(y, freq = NA)
Arguments
y |
time series |
freq |
Frequency of the time series |
Details
By default, the WO-test combines the results of the QS-test and the kw-test, both calculated on the residuals of an automatic non-seasonal ARIMA model. If the p-value of the QS-test is below 0.01 or the p-value of the kw-test is below 0.002, the WO-test will classify the corresponding time series as seasonal.
If residuals=FALSE the autoarima settings are ignored.
If residuals=TRUE, a non-seasonal ARIMA model is estimated for the time series. And the residuals of the fitted model are used as input to the test statistic. If an automatic order selection is used, the Hyndman-Khandakar algorithm is employed with max(p)=max(q) <= 3.
Author(s)
Daniel Ollech
References
Ollech, D. and Webel, K. (forthcoming). An overall seasonality test. Deutsche Bundesbank's Discussion Paper series.
Ollech, D. and Webel, K. (2020). A random forest-based approach to identifying the most informative seasonality tests. Deutsche Bundesbank's Discussion Paper series 55/2020.
Examples
combined_test(ts(rnorm(120, 10,10), frequency=12))
combined_test(ts(rnorm(120, 10,10), frequency=7))