Recent Life Expectancy Divergence in Baltic Countries

Until the end of the 1990s, mortality patterns and trends in Estonia, Latvia and Lithuania were remarkably similar. However, from the year 2000 onwards, life expectancy trends in the three countries started to diverge. In particular, sustainable progress in Estonia over the period 2000–2007 contrasts with stagnation in Latvia, and even worsening trends in Lithuania. These contradictory changes seem to be mainly explained by contrasting dynamics in mortality from cardiovascular diseases, external causes of death and digestive system diseases. Whereas cardiovascular and external-cause mortality declined in Estonia and Latvia, worsening or stagnation of mortality from these causes of death was observed in Lithuania. The negative mortality changes in Lithuania were also reinforced by a striking increase in mortality from alcohol-related digestive system diseases. The findings suggest that the divergence in health trends between the three countries may be attributable to their varying degrees of success in implementing structural health care reforms and specific health policy measures. By contrast, the very recent improvement (since 2008) is parallel in the three countries and is largely because of the introduction of rather similar anti-alcohol measures.     

Modeling heavy-tailed,skewed and peaked uncertainty phenomena with bounded support

A prevalence of heavy-tailed, peaked and skewed uncertainty phenomena have been cited in literature dealing with economic, physics, and engineering data. This fact has invigorated the search for continuous distributions of this nature. In this paper we shall generalize the two-sided framework presented in Kotz and van Dorp (Beyond beta: other continuous families of distributions with bounded support and applications. World Scientific Press, Singapore, 2004) for the construction of families of distributions with bounded support via a mixture technique utilizing two generating densities instead of one. The family of Elevated Two-Sided Power (ETSP) distributions is studied as an instance of this generalized framework. Through a moment ratio diagram comparison, we demonstrate that the ETSP family allows for a remarkable flexibility when modeling heavy-tailed and peaked, but skewed, uncertainty phenomena. We shall demonstrate its applicability via an illustrative example utilizing 2008 US income data.     

A computational framework for empirical Bayes inference

In empirical Bayes inference one is typically interested in sampling from the posterior distribution of a parameter with a hyper-parameter set to its maximum likelihood estimate. This is often problematic particularly when the likelihood function of the hyper-parameter is not available in closed form and the posterior distribution is intractable. Previous works have dealt with this problem using a multi-step approach based on the EM algorithm and Markov Chain Monte Carlo (MCMC). We propose a framework based on recent developments in adaptive MCMC, where this problem is addressed more efficiently using a single Monte Carlo run. We discuss the convergence of the algorithm and its connection with the EM algorithm. We apply our algorithm to the Bayesian Lasso of Park and Casella (J. Am. Stat. Assoc. 103:681–686, 2008) and on the empirical Bayes variable selection of George and Foster (J. Am. Stat. Assoc. 87:731–747, 2000).     

Epsilon Birnbaum–Saunders distribution family: properties and inference

In this paper we introduce a new extension for the Birnbaum–Saunder distribution based on the family of the epsilon-skew-symmetric distributions studied in Arellano-Valle et al. (J Stat Plan Inference 128(2):427–443, 2005). The extension allows generating Birnbaun–Saunders type distributions able to deal with extreme or outlying observations (Dupuis and Mills, IEEE Trans Reliab 47:88–95, 1998). Basic properties such as moments and Fisher information matrix are also studied. Results of a real data application are reported illustrating good fitting properties of the proposed model.     

A study of Bayesian local robustness with applications in actuarial statistics

Local or infinitesimal Bayesian robustness is a powerful tool to study the sensitivity of posterior magnitudes, which cannot be expressed in a simple manner. For these expressions, the global Bayesian robustness methodology does not seem adequate since the practitioner cannot avoid using inappropriate classes of prior distributions in order to make the model mathematically tractable. This situation occurs, for example, when we compute some types of premiums in actuarial statistics in order to fix the premium to be charged to an insurance policy. In this paper, analytical and simple expressions that allow us to study the sensitivity of premiums, which are usually used in automobile insurance are provided by using the local Bayesian robustness methodology. Some examples are examined by using real automobile claim insurance data.     

Départ Des Enfants Et Contraction Des Familles D'Après Les Recensements Canadiens De 1971 Et De 1981

Censuses do not usually collect information on the departure of children and the consequent contraction of the family; however, they sometimes do include useful information on these phenomena and their evolution. On these questions this article presents a new use of the 1971 and 1981 Canadian censuses. From the analysis, it is estimated that the timing of children's departure from their family of origin was almost the same in 1981 as in 1971; median age at departure was identical: 20.5 for women and 22.3 for men. Broken families, more numerous than in the past, become contracted earlier than unbroken families; among unbroken families, the contraction phase started earlier in 1981 than in 1971 among large or medium-sized families while it began later among small families. The method developed here succeeds with the Canadian data in palliating the lack of surveys; it would be interesting to test it on data from other Western societies.     

Passage a l'age adulte et mobilite spatiale

Starting with longitudinal data on two cohorts of women living in the Alpes-Maritimes in 1982 (a sample of 1,500 women in total) we try to establish the role of the spatial distribution of opportunities at a number of key stages in the life cycle: marriage, birth of first child, making professional use of qualifications, confrontation of a situation of professional risk and professional mobility during the years immediately following the completion of studies. The underlying hypothesis is that control of social location often depends on the control of spatial location.     

Simulating space-time random fields with nonseparable Gneiting-type covariance functions

Statistics and Computing - Two algorithms are proposed to simulate space-time Gaussian random fields with a covariance function belonging to an extended Gneiting class, the definition of which...