| kw {seastests} | R Documentation |
Kruskall Wallis test
Description
Test for seasonality in a time series.
Usage
kw(x, freq = NA, diff = T, residuals = F, autoarima = T)
Arguments
x |
time series |
freq |
Frequency of the time series |
diff |
Shall the differenced series be tested? |
residuals |
Shall the residuals of an ARIMA model be tested? |
autoarima |
Use automatic instead of a (0,1,1) ARIMA model? |
Details
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
Hyndman, R. J. and Y. Khandakar (2008). Automatic Time Series Forecasting: The forecast Package for R. Journal of Statistical Software 27 (3), 1-22.
Kruskal, W. H. and W. A. Wallis (1952). Use of Ranks in One-Criterion Variance Analysis. Journal of the American Statistical Association 47 (260), 583-621.
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
kw(ts(rnorm(120, 10,10), frequency=12))
kw(ts(rnorm(1200, 10,10), frequency=7))