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70 – Nonlinearites and Information
A Spectral-Based Kolmogorov-Smirnov Method for Detecting the Information Loss of Temporal Aggregation
Sponsor: Business and Economic Statistics Section
Keywords: temporal aggregation, information loss, spectral analysis, Kolmogorov-Smirnov test, time series
Bu Hyoung Lee
Loyola University Maryland
In this article, we develop a spectral method for identifying information loss on the process characteristics of an aggregate series. Even though temporal aggregation is a simple and efficient technique summarizing sequential observations, it causes substantial structural changes in a process because a non-aggregate series of a relatively high frequency is transformed into an aggregate series of a relatively low frequency. The effects of temporal aggregation can be explained with changes in the spectral density function. Then, we propose a spectral-based Kolmogorov-Smirnov test for detecting an aggregation resulting significant structural changes to white noise.