Application of Approximate Bayesian Computational for Estimate Parameter and Selection Model in Dynamic of HIV
DOI:
https://doi.org/10.53660/CONJ-982-813CResumo
A aplicação de técnicas Bayesianas tem se tronado comum em bioengenharia, é comum realizar inferências sobre parâmetros e variáveis de estado que não podem ser mensurados. Este trabalho tem como objetivo aplicar a técnica de Aproximação Bayesiana Computacional para estimar parâmetros e selecionar modelos simultaneamente nos modelos que descreve a dinâmica de células importantes que representam o HIV. Três diferentes modelos dinâmicos foram usados para avaliar a verificação do algoritmo, esta verificação foi realizada com medidas simuladas. A técnica foi verificada e se mostrou ser robusta o suficiente para estimar parâmetros e selecionar o melhor modelo simultaneamente e por isso, esta se mostra ser uma técnica promissora.
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