Abstract
In this article, we study the empirical power of Bartlett's Kolmogorov–Smirnov test statistic derived from cumulative periodograms in detecting chaos. In our study, we simulated 10 000 time series of i.i.d. standard normal random variable, logistic map and Gaussian chaotic map of various lengths with and without measurement errors. The empirical power was assessed for the original series and its order transformed series. Although our results showed that the Bartlett's test statistic was not a powerful test statistic in detecting chaos when it is applied directly to the original series generated by the logistic map and the Gaussian chaotic map, the order transformation technique can significantly increase the power of the Bartlett's test statistic.
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