Comparing non-stationary and irregularly spaced time series

Authors:
Gladys E. Salcedo;RogéRio F. Porto;Pedro A. Morettin
Affiliations:
Department of Mathematics, University of Quindío, Colombia;Bank of Brazil, Brasília, Brazil;Institute of Mathematics and Statistics, University of São Paulo, Brazil
Venue:
Computational Statistics & Data Analysis
Year:
2012

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Abstract

In this paper, we present approximate distributions for the ratio of the cumulative wavelet periodograms considering stationary and non-stationary time series generated from independent Gaussian processes. We also adapt an existing procedure to use this statistic and its approximate distribution in order to test if two regularly or irregularly spaced time series are realizations of the same generating process. Simulation studies show good size and power properties for the test statistic. An application with financial microdata illustrates the test usefulness. We conclude advocating the use of these approximate distributions instead of the ones obtained through randomizations, mainly in the case of irregular time series.