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https://doi.org/10.1080/10485250902878655

has been cited by the following article:

• TITLE: Goodness-of-Fit Test for Non-Stationary and Strongly Dependent Samples

  AUTHORS: Carolina Crisci, Gonzalo Perera, Lia Sampognaro

  KEYWORDS: Kolmogorov-Smirnov Test, Strongly Dependent Data, Asymptotic Behavior of Empirical Processes

  JOURNAL NAME: Advances in Pure Mathematics, Vol.13 No.5, May 15, 2023

  ABSTRACT: In this article we improve a goodness-of-fit test, of the Kolmogorov-Smirnov type, for equally distributed- but not stationary-strongly dependent data. The test is based on the asymptotic behavior of the empirical process, which is much more complex than in the classical case. Applications to simulated data and discussion of the obtained results are provided. This is, to the best of our knowledge, the first result providing a general goodness of fit test for non-weakly dependent data.