Distributions of pattern statistics in sparse Markov models
type: Item
instance of: scholarly article
title: Distributions of pattern statistics in sparse Markov models
zbMATH Open document ID: 1447.62103
author: Donald E. K. Martin
published in: Annals of the Institute of Statistical Mathematics
publication date: 2020-07-20T00:00:00Z
review text: A time series \(\mathbf{X}\) that takes values in a finite set \(\Sigma\) is modelled by an \(m\)th-order Markov sequence; this may be embedded in a first-order Markov chain, at the price of specifying \(|\Sigma|^m\,(|\Sigma|-1)\) transition probabilities. Moreover Markov models allow fairly few choices for the number of model parameters. The author considers Sparse Markov Models (see Definition 1) which allow to group conditioning histories into classes such that the conditional probability distribution is constant for the members of each class. The methodology for efficient computation of pattern distributions is extended to the sparse Markov framework.
reviewed by: Carlo Sempi
Mathematics Subject Classification ID: 62M10
Mathematics Subject Classification ID: 62M02
Mathematics Subject Classification ID: 60J10
zbMATH DE Number: 7223265
zbMATH Keywords: sparse Markov model
zbMATH Keywords: pattern distribution
zbMATH Keywords: variable length Markov chain
describes a project that uses: PatternHunter
MaRDI profile type: Publication
full work available at URL: s10463-019-00714-6
OpenAlex ID: W2928269031
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Wikidata QID: Q128095680
DOI: 10.1007/S10463-019-00714-6
description: scientific article; zbMATH DE number 7223265