publication . Article . Other literature type . 2000

a sufficiency property arising from the characterization of extremes of markov chains

Bortot, Paola; Coles, Stuart;
  • Published: 01 Feb 2000 Journal: Bernoulli, volume 6, page 183 (issn: 1350-7265, Copyright policy)
  • Publisher: JSTOR
At extreme levels, it is known that for a particular choice of marginal distribution, transitions of a Markov chain behave like a random walk. For a broad class of Markov chains, we give a characterization for the step length density of the limiting random walk, which leads to an interesting sufficiency property. This representation also leads us to propose a new technique for kernel density estimation for this class of models.
free text keywords: Statistics and Probability, Markov model, Markov chain mixing time, Random walk, Variable-order Markov model, Markov kernel, Statistics, Markov property, Markov chain, Mathematics, Markov renewal process, extreme value theory, kernel density estimation, sufficient statistics
Related Organizations
Powered by OpenAIRE Research Graph
Any information missing or wrong?Report an Issue