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Fitting DNA sequences through log-linear modelling with linear constraints

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Martín Apaolaza, Níriam and Pardo Llorente, Leandro (2011) Fitting DNA sequences through log-linear modelling with linear constraints. Statistics, 45 (6). pp. 605-621. ISSN 0233-1888

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Official URL: http://www.tandfonline.com/doi/pdf/10.1080/02331888.2010.485275


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Abstract

For some discrete state series, such as DNA sequences, it can often be postulated that its probabilistic behaviour is given by a Markov chain. For making the decision on whether or not an uncharacterized piece of DNA is part of the coding region of a gene, under the Markovian assumption, there are two statistical tools that are essential to be considered: the hypothesis testing of the order in a Markov chain and the estimators of transition probabilities. In order to improve the traditional statistical procedures for both of them when stationarity assumption can be considered, a new version for understanding the homogeneity hypothesis is proposed so that log-linear modelling is applied for conditional independence jointly with homogeneity restrictions on the expected means of transition counts in the sequence. In addition we can consider a variety of test-statistics and estimators by using phi-divergence measures. As special case of them the well-known likelihood ratio test-statistics and maximum-likelihood estimators are obtained.


Item Type:Article
Uncontrolled Keywords:contingency table; log-linear model; restricted estimator; conditional test statistic; Maximum-likelihood methods
Subjects:Sciences > Mathematics > Mathematical statistics
ID Code:17348
Deposited On:10 Dec 2012 09:06
Last Modified:25 Jul 2018 11:07

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