Composite Likelihood Estimation for Multivariate Probit Latent Traits Models

Inference in generalized linear mixed models with multivariate random effects is often made cumbersome by the high-dimensional intractable integrals involved in the marginal likelihood. This article presents an inferential methodology based on the marginal composite likelihood approach for the probit latent traits models. This method belonging to the broad class of pseudo-likelihood involves marginal pairs probabilities of the responses which has analytical expression. The different results are illustrated with a simulation study and with an analysis of real data from health related quality of life.     

A slack analysis framework for improving composite indicators with applications to human development and sustainable energy indices

Data envelopment analysis models are used for measuring composite indicators in various areas. Although there are many models for measuring composite indicators in the literature, surprisingly, there is no methodology that clearly shows how composite indicators improvement could be performed. This article proposes a slack analysis framework for improving the composite indicator of inefficient entities. For doing so, two dual problems originated from two data envelopment analysis models in the literature are proposed, which can guide decision makers on how to adjust the subindicators of inefficient entities to improve their composite indicators through identifying which subindicators must be improved and how much they should be augmented. The proposed methodology for improving composite indicators is inspired from data envelopment analysis and slack analysis approaches. Applicability of the proposed methodology is investigated for improving two well-known composite indicators, i.e., Sustainable Energy Index and Human Development Index. The results show that 12 out of 18 economies are inefficient in the context of sustainable energy index, for which the proposed slack analysis models provide the suggested adjustments in terms of their respected subindicators. Furthermore, the proposed methodology suggests how to adjust the life expectancy, the education, and the gross domestic product (GDP) as the three socioeconomic indicators to improve the human development index of 24 countries which are identified as inefficient entities among 27 countries.     

On control charts for monitoring the variance of a time series

In this paper we derive control charts for the variance of a Gaussian process using the likelihood ratio approach, the generalized likelihood ratio approach, the sequential probability ratio method and a generalized sequential probability ratio procedure, the Shiryaev–Roberts procedure and a generalized modified Shiryaev–Roberts approach. Recursive presentations for the calculation of the control statistics are given for autoregressive processes of order 1. In an extensive simulation study these schemes are compared with existing control charts for the variance. In order to asses the performance of the schemes both the average run length and the average delay are used.     

Copula-based regression models: A survey

In this review paper we collect several results about copula-based models, especially concerning regression models, by focusing on some insurance applications.