seasonal.test {nortsTest}

The Seasonal unit root tests function

Description

Perform a seasonal unit root test to check seasonality in a linear stochastic process

Usage

seasonal.test(y, seasonal = c("ocsb","ch","hegy"), alpha = 0.05)

Arguments

y

a numeric vector or an object of the ts class containing a stationary time series.

seasonal

A character string naming the desired seasonal unit root test for checking seasonality. Valid values are "ocsb" for the Osborn, Chui, Smith, and Birchenhall, "ch" for the Canova and Hansen, and "hegy" for Hylleberg, Engle, Granger, and Yoo. The default value is "ocsb" for the Osborn, Chui, Smith, and Birchenhall test.

alpha

Level of the test, possible values range from 0.01 to 0.1. By default alpha = 0.05 is used

Details

Several different tests are available: In the kpss test, the null hypothesis that y has a stationary root against a unit-root alternative. In the two remaining tests, the null hypothesis is that y has a unit root against a stationary root alternative. By default, alpha = 0.05 is used to select the more likely hypothesis.

Value

A list with class "h.test" containing the following components:

statistic:

the test statistic.

parameter:

the test degrees freedoms.

p.value:

the p-value for the test.

alternative:

a character string describing the alternative hypothesis.

method:

a character string with the test name.

data.name:

a character string giving the name of the data.

Author(s)

Asael Alonzo Matamoros

References

Osborn, D., Chui, A., Smith, J., & Birchenhall, C. (1988). Seasonality and the order of integration for consumption. Oxford Bulletin of Economics and Statistics. 50(4), 361-377.

Canova, F. & Hansen, B. (1995). Are Seasonal Patterns Constant over Time? A Test for Seasonal Stability. Journal of Business and Economic Statistics. 13(3), 237-252.

Hylleberg, S., Engle, R., Granger, C. & Yoo, B. (1990). Seasonal integration and cointegration. Journal of Econometrics 44(1), 215-238.

See Also

normal.test, uroot.test

Examples

#  stationary  ar process
y = ts(rnorm(100),frequency = 6)
seasonal.test(y)