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A MARKOV CHAIN MODEL FOR MAGAZINE EXPOSURE
Author(s) -
Danaher Peter J.
Publication year - 1990
Publication title -
australian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 41
eISSN - 1467-842X
pISSN - 0004-9581
DOI - 10.1111/j.1467-842x.1990.tb01010.x
Subject(s) - markov chain , markov model , beta binomial distribution , negative binomial distribution , bernoulli's principle , statistics , markov chain mixing time , bernoulli trial , econometrics , variable order markov model , markov chain monte carlo , maximum likelihood , markov property , mathematics , computer science , engineering , bayesian probability , poisson distribution , aerospace engineering
Summary Klotz's (1973) Markov chain model for dependent Bernoulli trials is applied to magazine exposure distributions. Simple parameter estimates are derived and are shown to compare well with the maximum likelihood estimates. The Markov model is fitted to forty magazines from a large print media survey and compares favourably with the most popular non‐proprietary magazine model, the beta‐binomial model. In addition, the Markov model is used to simulate magazine exposure distributions.