Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1150270 | Journal of Statistical Planning and Inference | 2006 | 10 Pages |
Abstract
We address the problem of nonparametric testing of serial independence for time series and its generalization. More precisely, we consider a stationary and ergodic source p, which generates symbols x1â¦xt from some finite set A and a null hypothesis H0 that p is a Markov source of order at most m,(m⩾0). The alternative hypothesis H1 is that the sequence is generated by a stationary and ergodic source, which differs from the source under H0. In particular, if m=0 we have the null hypothesis H0 that the sequence is generated by a Bernoulli source (i.e. the hypothesis that x1â¦xt are independent). In this paper some new tests that are based on so-called universal codes and universal predictors, are suggested.
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Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Boris Ryabko, Jaakko Astola,