Finally a set of colorectal cancer data is considered to show the applicability of the model, in which, compared to other models, the proposed model best fits this dataset. Un ejemplo muy claro de ello son las medallas en una competicin, las cuales (bronce, plata, oro), pese a no ser cuantitativas, s que siguen un orden esperado. In addition, simulation studies were performed to evaluate the performance of the classical and Bayesian estimates of the model parameters, in which the maximum likelihood estimators of the model parameters satisfy the asymptotic properties. The classical inference is based on the theory of maximum likelihood, and the Bayesian inference is based on the Markov chain Monte Carlo method. Inferential procedures are developed from a classical and Bayesian perspective.

The new family is extended to regression models, in which the model is reparametrized in the median of the response variable and together with the dispersion parameter are related to covariables through a link function. For the new model its structural properties are studied. En definitiva, en estadstica la agrupacin de datos sirve para analizar conjuntamente varios datos, de manera que los datos agrupados en un intervalo se tratan como un solo dato. The proposed model is constructed under a transformation of variables, in which the transformed variable is the result of the combination of a variable with standard normal distribution and the cumulative distribution function of the generalized extreme value distribution. Um intervalo de data armazena, tanto uma quantidade de tempo (em anos, meses, dias, horas, etc), quanto uma string de tempo relativo no formato que o. As pues, al agrupar un conjunto de datos estadsticos se separan en diferentes intervalos, de manera que cada dato solo puede pertenecer a un nico intervalo. In this research a new statistical model is introduced to model data restricted in the continuous interval (0,1).

Intervalo de variable