Parameter estimation in hidden variable models for the multiple alignment of biological sequences

• Autores: Ana Arribas Gil
• Localización: XXX Congreso Nacional de Estadística e Investigación Operativa y de las IV Jornadas de Estadística Pública: actas, 2007, ISBN 978-84-690-7249-3
• Idioma: inglés
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• Resumen

  • In this paper we deal with parameter estimation in a multiple alignment model defined from a classical sequence evolution process. We first provide a rigorous formalism for the homology structure of k sequences related by a star tree and discuss possible definitions of likelihoods. Existence of two different Information divergence rates is established and a divergence property is shown under additional assumptions. This yields consistency for the parameter in parametrization schemes for which the divergence property holds. Simulations illustrate different cases which are not covered by our results.