The main aim of this work is to develop alternative queuing models to M/ G/l, in which arrivals follow a Poisson process, the total number of customers on the system and the total number of service channels are unknown. ...

The present work's main objective is to study the significance of zeros in an observable and latent data. In observable data set that occur excess of zeros, its common to have sobredispersion. In this sense, the models ...

In this thesis, we introduce a methodology based on zero-inflated survival data for the purposes of dealing with propensity to default (credit risk) in bank loan portfolios. Our approach enables us to accommodate three ...

In this thesis new families of survival distributions are proposed. Those distributions are derived by assuming a latent activation structure to explain the occurrence of the event of interest. In general, the competitive ...

We know that statistic modeling by regression had a stronger impulse since generalized linear models (GLMs) development in 70 decade beginning of the XX century, proposed by Nelder e Wedderburn (1972). GLMs theory can be ...

Modeling of a cure fraction, also known as long-term survivors, is a part of survival analysis. It studies cases where supposedly there are observations not susceptible to the event of interest. Such cases require special ...

In this thesis, we extend the analysis of multivariate Seemingly Unrelated Regression (SUR) Tobit models by modeling their nonlinear dependence structures through copulas. The capability in coupling together the diferent ...

Accurate and robust forecasting methods for univariate time series are critical as the historical data can be used in the strategic planning of such future operations as buying and selling to ensure product inventory and ...

From the generalized normal distribution and concepts of the generalized autoregressive moving averages models we introduce the generalized normal-ARMA model as an alternative way to model time series exhibiting symmetry ...