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| Format: | Artículo científico |
| Language: | en |
| Published: |
Universidad Nacional de Colombia
2011
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| Online Access: | https://www.redalyc.org/articulo.oa?id=89921357009 |
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Table of Contents:
- On the Student-t Mixture Inverse Gaussian Model with an Application to Protein Production Antonio Sanhueza Víctor Leiva Liliana López-Kleine Física, Astronomía y Matemáticas Length biased distributions Likelihood methods R computer language In this article, we introduce a mixture inverse Gaussian (MIG) model based on the Student-t distribution and apply it to bacterium-based protein production for food industry. This model is mainly useful to describe data that follow positively skewed distributions and accommodate atypical observations in a better way than its classical version. Specifically, we present a characterization of the MIG-t distribution. In addition, we carry out a hazard analysis of this distribution centered mainly on its hazard rate. Furthermore, we discuss the maximum likelihood method, which produces-in this case-robust parameter estimates. Moreover, to evaluate the potential influence of atypical observations, we produce a diagnostic analysis for the model. Finally, we apply the obtained results to novel bacterium-based proteinproduction data and statistically compare two types of protein producers using the likelihood ratio test based on the MIG-t model as an alternative methodology to the procedures available until now. This fact is very important, since the evaluation of protein production using both constructions allows practitioners to choose the most productive one before the bacterial culture is scaled to an industrial level. 2011 artículo científico 0120-1751 https://www.redalyc.org/articulo.oa?id=89921357009 en http://www.redalyc.org/revista.oa?id=899 Revista Colombiana de Estadística application/pdf Universidad Nacional de Colombia Revista Colombiana de Estadística (Colombia) Num.1 Vol.34