A MARKOV CHAIN MODEL FOR MAGAZINE EXPOSURE

Peter J. Danaher

doi:10.1111/j.1467-842X.1990.tb01010.x

A MARKOV CHAIN MODEL FOR MAGAZINE EXPOSURE

Peter J. Danaher

Research output: Contribution to journal › Article › Research › peer-review

1 Citation (Scopus)

Abstract

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.

Original language	English
Pages (from-to)	163-176
Number of pages	14
Journal	Australian Journal of Statistics
Volume	32
Issue number	2
DOIs	https://doi.org/10.1111/j.1467-842X.1990.tb01010.x
Publication status	Published - 1 Jan 1990
Externally published	Yes

Keywords

Beta‐binomial
magazine exposure distribution
Markov chain
modified beta‐binomial
simulation

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10.1111/j.1467-842X.1990.tb01010.x

Cite this

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AB - 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.

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KW - simulation

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A MARKOV CHAIN MODEL FOR MAGAZINE EXPOSURE

Abstract

Keywords

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