%0 Journal Article
%T Goodness-of-Fit Test for Non-Stationary and Strongly Dependent Samples
%A Carolina Crisci
%A Gonzalo Perera
%A Lia Sampognaro
%J Advances in Pure Mathematics
%P 226-236
%@ 2160-0384
%D 2023
%I Scientific Research Publishing
%R 10.4236/apm.2023.135016
%X 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.
%K Kolmogorov-Smirnov Test
%K Strongly Dependent Data
%K Asymptotic Behavior of Empirical Processes
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=124868