Two alternative estimation procedures for the negative binomial cure rate model with a latent activation scheme

In this paper two alternative estimation procedures based on the EM algorithm are proposed forthe flexible negative binomial cure rate model with a latent activation scheme. The Weibull modelas well as the log-normal and gamma distributions are also considered for the time-to-event datafor the non-destroyed cells. Simulation studies show the satisfactory performance of the proposedmethodology. The impact of misspecifying the survival function on both components of the model(cured and susceptible) is also evaluated. The use of the new methodology is illustrated with areal data set related to a clinical trial on Phase III cutaneous melanoma patients

Flexible Birnbaum-Saunders distribution

In this paper, we propose a bimodal extension of the Birnbaum–Saunders model by including an extra parameter. This new model is termed flexible Birnbaum–Saunders (FBS) and includes the ordinary Birnbaum–Saunders (BS) and the skew Birnbaum–Saunders (SBS) model as special cases. Its properties are studied. Parameter estimation is considered via an iterative maximum likelihood approach. Two real applications, of interest in environmental sciences, are included, which reveal that our proposal can perform better than other competing models.Ministerio de Economía y Competitividad (MINECO). Españ

An extension of the slash-elliptical distribution

This paper introduces an extension of the slash-elliptical distribution. This new distribution is generated as the quotient between two independent random variables, one from the elliptical family (numerator) and the other (denominator) a beta distribution. The resulting slash-elliptical distribution potentially has a larger kurtosis coefficient than the ordinary slash-elliptical distribution. We investigate properties of this distribution such as moments and closed expressions for the density function. Moreover, an extension is proposed for the location scale situation. Likelihood equations are derived for this more general version. Results of a real data application reveal that the proposed model performs well, so that it is a viable alternative to replace models with lesser kurtosis flexibility. We also propose a multivariate extension

Likelihood-based inference for the power regression model

In this paper we investigate an extension of the power-normal model, called the alpha-power model and specialize it to linear and nonlinear regression models, with and without correlated errors. Maximum likelihood estimation is considered with explicit derivation of the observed and expected Fisher information matrices. Applications are considered for the Australian athletes data set and also to a data set studied in Xie et al. (2009). The main conclusion is that the proposed model can be a viable alternative in situations were the normal distribution is not the most adequate model

The Operational Baysean Approach for Finite Populations

In this paper we discuss invariant prediction in finite populations. It is assumed that the distribution of the observable quantities is invariant under an orthogonal group of transformations

Influence diagnostics in exponentiated-Weibull regression models with censored data.

Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as departures from the error assumptions and the presence of outliers and influential observations with the fitted models. The literature provides plenty of approaches for detecting outlying or influential observations in data sets. In this paper, we follow the local influence approach (Cook 1986) in detecting influential observations with exponentiated-Weibull regression models. The relevance of the approach is illustrated with a real data set, where it is shown that by removing the most influential observations, there is a change in the decision about which model fits the data better.Peer Reviewe

Influence diagnostics in exponentiated-Weibull regression models with censored data

Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as departures from the error assumptions and the presence of outliers and influential observations with the fitted models. The literature provides plenty of approaches for detecting outlying or influential observations in data sets. In this paper, we follow the local influence approach (Cook 1986) in detecting influential observations with exponentiated-Weibull regression models. The relevance of the approach is illustrated with a real data set, where it is shown that by removing the most influential observations, there is a change in the decision about which model fits the data better

A note on the likelihood and moments of the skew-normal distribution

In this paper an alternative approach to the one in Henze (1986) is proposed for deriving the odd moments of the skew-normal distribution considered in Azzalini (1985). The approach is based on a Pascal type triangle, which seems to greatly simplify moments computation. Moreover, it is shown that the likelihood equation for estimating the asymmetry parameter in such model is generated as orthogonal functions to the sample vector. As a consequence, conditions for a unique solution of the likelihood equation are established, which seem to hold in more general setting.Peer Reviewe