chksea: Check the Seasonality of Each Component of a Multiple Time...

In SLBDD: Statistical Learning for Big Dependent Data

Check the Seasonality of Each Component of a Multiple Time Series

Description

Check the seasonality of each component of a multiple time series.

Usage

chksea(x, period = c(12), p = 0, alpha = 0.05, output = TRUE)

Arguments

x	T by k data matrix: T data points in rows with each row being data at a given time point, and k time series in columns.
period	seasonal period. Default value is 12.
p	Regular AR order. Default value is max(floor(log(T)),1).
alpha	Type-I error for the t-ratio of seasonal coefficients. Default value is 0.05.
output	If TRUE it returns if the series has seasonality. Default is TRUE.

Details

Check the seasonality fitting a seasonal AR(1) model and a regular AR(p) model to a scalar time series and testing if the estimated seasonal AR coefficient is significant.

Value

A list containing:

• Seasonal - TRUE or FALSE.

• period - Seasonal period.

Examples

data(TaiwanAirBox032017)
output <- chksea(TaiwanAirBox032017[,1])

SLBDD documentation built on April 27, 2022, 5:08 p.m.