seasdum: F-Test on seasonal dummies

Description Usage Arguments Details Author(s) References Examples

View source: R/seasdum.R

Description

Test for seasonality in a time series based on joint significance seasonal dummies in a non-seasonal ARIMA model.

Usage

1
seasdum(x, freq = NA, autoarima = FALSE)

Arguments

x

time series

freq

Frequency of the time series

autoarima

Use automatic instead of a (0,1,1) ARIMA model?

Details

A RegARIMA model is estimated with (0,1,1)+Seasonal dummies if autoarima=FALSE (default) or (p,d,q)+Seasonal dummies if autoarima=TRUE, (p,d,q) selected by Hyndman-Khandakar algorithm with max(p)=max(q) <= 3. Then the tests checks whether the seasonal dummies are jointly different from zero, i.e. whether deterministic seasonality can be detected in the time series.

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.

Maravall, A. (2011). Seasonality Tests and Automatic Model Identification in TRAMO-SEATS. Bank of Spain.

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

1
2
seasdum(ts(rnorm(120, 10,10), frequency=12))
seasdum(ts(rnorm(70, 10,10), frequency=7))

Example output

Test used:  SeasonalDummies 
 
Test statistic:  1.71 
P-value:  0.08018539
Test used:  SeasonalDummies 
 
Test statistic:  0.52 
P-value:  0.7909344

seastests documentation built on Sept. 18, 2021, 5:07 p.m.

Related to seasdum in seastests...