Estimation and influence diagnostics for zero-inflated hyper-Poisson regression model: full Bayesian analysis

The purpose of this paper is to develop a Bayesian analysis for the zero-inflated hyper-Poisson model. Markov chain Monte Carlo methods are used to develop a Bayesian procedure for the model and the Bayes estimators are compared by simulation with the maximum-likelihood estimators. Regression modeling and model selection are also discussed and case deletion influence diagnostics are developed for the joint posterior distribution based on the functional Bregman divergence, which includes ψ-divergence and several others, divergence measures, such as the Itakura–Saito, Kullback–Leibler, and χ² divergence measures. Performance of our approach is illustrated in artificial, real apple cultivation experiment data, related to apple cultivation.     

Political Influence and the Performance of Nonprofit Spanish Banks

This article presents empirical evidence about factors that influence the solvency of Spanish savings banks. It also studies whether the presence of politicians in their governance has led to lower solvency ratios and, consequently, to the current economic situation in the Spanish banking sector. We use multivariate regressions, taking the solvency ratio as the dependent variable; and efficiency, the coverage ratio, political influence, CEOs’ political influence, size, growth, and age as independent variables. Our results confirm that banking entities controlled by politicians resulted in poor performance, and political influence on the boards of savings banks led them to insolvency. The findings show that the non‐ownership structure of savings banks, the lack of best practice corporate governance mechanisms, and political presence have weakened them.     

The odd log-logistic Lindley Poisson model for lifetime data

We define two new lifetime models called the odd log-logistic Lindley (OLL-L) and odd log-logistic Lindley Poisson (OLL-LP) distributions with various hazard rate shapes such as increasing, decreasing, upside-down bathtub, and bathtub. Various structural properties are derived. Certain characterizations of OLL-L distribution are presented. The maximum likelihood estimators of the unknown parameters are obtained. We propose a flexible cure rate survival model by assuming that the number of competing causes of the event of interest has a Poisson distribution and the time to event has an OLL-L distribution. The applicability of the new models is illustrated by means real datasets.     

A nonlinear regression model with skew-normal errors

In this paper we have discussed inference aspects of the skew-normal nonlinear regression models following both, a classical and Bayesian approach, extending the usual normal nonlinear regression models. The univariate skew-normal distribution that will be used in this work was introduced by Sahu et al. (Can J Stat 29:129–150, 2003), which is attractive because estimation of the skewness parameter does not present the same degree of difficulty as in the case with Azzalini (Scand J Stat 12:171–178, 1985) one and, moreover, it allows easy implementation of the EM-algorithm. As illustration of the proposed methodology, we consider a data set previously analyzed in the literature under normality.     

Bayesian analysis of skew-t multivariate null intercept measurement error model

The multivariate skew-t distribution (J Multivar Anal 79:93–113, 2001; J R Stat Soc, Ser B 65:367–389, 2003; Statistics 37:359–363, 2003) includes the Student t, skew-Cauchy and Cauchy distributions as special cases and the normal and skew–normal ones as limiting cases. In this paper, we explore the use of Markov Chain Monte Carlo (MCMC) methods to develop a Bayesian analysis of repeated measures, pretest/post-test data, under multivariate null intercept measurement error model (J Biopharm Stat 13(4):763–771, 2003) where the random errors and the unobserved value of the covariate (latent variable) follows a Student t and skew-t distribution, respectively. The results and methods are numerically illustrated with an example in the field of dentistry.     

Robust linear mixed models with skew-normal independent distributions from a Bayesian perspective

Linear mixed models were developed to handle clustered data and have been a topic of increasing interest in statistics for the past 50 years. Generally, the normality (or symmetry) of the random effects is a common assumption in linear mixed models but it may, sometimes, be unrealistic, obscuring important features of among-subjects variation. In this article, we utilize skew-normal/independent distributions as a tool for robust modeling of linear mixed models under a Bayesian paradigm. The skew-normal/independent distributions is an attractive class of asymmetric heavy-tailed distributions that includes the skew-normal distribution, skew-t, skew-slash and the skew-contaminated normal distributions as special cases, providing an appealing robust alternative to the routine use of symmetric distributions in this type of models. The methods developed are illustrated using a real data set from Framingham cholesterol study.     

COM–Poisson cure rate survival models and an application to a cutaneous melanoma data

In this paper, we develop a flexible cure rate survival model by assuming the number of competing causes of the event of interest to follow the Conway–Maxwell Poisson distribution. This model includes as special cases some of the well-known cure rate models discussed in the literature. Next, we discuss the maximum likelihood estimation of the parameters of this cure rate survival model. Finally, we illustrate the usefulness of this model by applying it to a real cutaneous melanoma data.     

Capital goods imports and long-run growth: Is the Chinese experience relevant to developing countries?

In this paper, we analyze the role played by capital goods imports in the long-run growth of developing countries. We focus in the case of the Chinese economy in the last few decades. We find evidence that the ratio of imported to domestic capital goods, that is, the composition of investment, as well as the capital accumulation (both physical and human), was key determinants of the long-run growth rate of per capita GDP over the analyzed period. Furthermore, our results are also consistent with the hypothesis that the link between trade openness and long-run growth operates mainly through imports. This finding supports some recent developments of Schumpeterian models of growth, and the very specific economic policy recommendations arising thereof. In short, these models state that, in the early stages of growth, government intervention to encourage an investment-based strategy, with emphasis on large investment efforts and the adoption of foreign technology, could be an appropriate strategy for development.     

Results of a Quality of Work Life Index in Spain. A Comparison of Survey Results and Aggregate Social Indicators

The European Union launched the Lisbon Strategy in 2000 with the aim of establishing itself as the world’s most powerful economy. The importance of job quality has returned to the top of the European employment and social policy agenda. As targets are set, significant progress has been made in the creation of indicators. In this study, we compute a composite index for quality of work life using the dimensional structure provided by the European Commission, and present our results for regions, sectors, professional categories and sizes of firm in Spain in the period 2001–2004. We find that better results are found in the more developed regions, in service sectors, in bigger firms and in jobs with more responsibility. Finally, we compare the results of the index with workers’ subjective perceptions of job satisfaction, measured by a quality of work life survey. The test results reveal a strong relationship between the two measurements.