Boletim do resumo e programas (XIV EMR 2015)

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XIV Escola de Modelos de Regressão De 2 a 5 de Março de 2015 - Centro de Convenções - Unicamp 49 Comunicação Oral 7.2 ( CO7) The odd log-logistic normal distribution: theory and applications in analysis of experiments Altemir da Silva Braga Gauss M. Cordeiro Edwin M. M. Ortega José Nilton da Cruz Resumo: Providing a new distribution is always precious for statisticians. A new three-parameter distribution called the odd log-logistic normal (OLLN) distribution is defined and studied. Various of its structural properties are derived including some explicit expressions for the moments, generating functions, mean deviations and incomplete moments. Maximum likelihood techniques are used to t the new model and to show its potentiality by means of three the real data sets in analysis of experiments. Based on three criteria, the proposed distribution provides a better t then the normal, skew normal, beta normal, Kumaraswamy normal and gamma normal distributions. Palavras-Chave: Log-logistic distribution; Maximum likelihood estimation; Mean deviation; Normal distribution. Auditório 1 Data Março 5 : emrxiv@gmail.com : http://www.ime.usp.br/~abe/emr2015
XIV Escola de Modelos de Regressão De 2 a 5 de Março de 2015 - Centro de Convenções - Unicamp 50 Comunicação Oral 7.3 ( CO7) The log-odd log-logistic Weibull regression model: modeling, estimation, influence diagnostics and residual analysis José Nilton da Cruz Edwin M. M. Ortega Gauss M. Cordeiro Ana K. Campelo Resumo: In survival analysis applications, the failure rate function may frequently present a unimodal shape. In such case, the log-normal and log-logistic distributions are used. In this paper, we shall be concerned only with parametric forms, so a location-scale regression model based on the odd log-logistic Weibull distribution is proposed for modeling data with a decreasing, increasing, unimodal and bathtub failure rate function as an alternative to the log-Weibull regression model. For censored data, we consider a classic method to estimate the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Further, for different parameter settings, sample sizes and censoring percentages, various simulations are performed. In addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be extended to a modified deviance residual in the proposed regression model applied to censored data. We analyze a real data set using the log-odd log-logistic Weibull regression model. Data Março 5 Auditório 1 : emrxiv@gmail.com : http://www.ime.usp.br/~abe/emr2015
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