Abstract

This article describes the R package costat. This package enables a user to (i) perform a test for time series stationarity; (ii) compute and plot time-localized autocovariances, and (iii) to determine and explore any costationary relationship between two locally stationary time series. Two locally stationary time series are said to be costationary if there exists two time-varying combination functions such that the linear combination of the two series with the functions produces another time series which is stationary. Costationarity existing between two time series indicates a relationship between the series that might be usefully exploited in a number of ways. Sometimes the relationship itself is of interest, sometimes the derived stationary series is of interest and useful as a substitute for either of the original stationary series in some applications.

Highlights

  • The costat package is designed for the analysis of locally stationary time series, locally stationary wavelet time series

  • Many are familiar with the concept of a stationary time series: that is, loosely speaking, a series whose statistical properties do not change over time

  • We should mention at this point that we are considering the testing of second-order stationarity of locally stationary time series

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Summary

Summary

The costat package is designed for the analysis of locally stationary time series, locally stationary wavelet time series. Computing tests of stationarity, BootTOS; computing localized autocovariances, lacv; discovering costationarity between two time series, findstysols. Several method functions exist that print, summarize or plot the various outputs of these functions

Introduction
The Test
Simulation Results
LACV on a stationary series
LACV on a simulated locally stationary series
LACV on a locally stationary series
Commands to discover costationarity
Plots for obtaining an overview of all solutions
Plotting information about individual solutions
Full Text
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