What Comes After the Prestige Disaster? An Entropic Approach to Modeling the Recurrence of Major Oil Tanker Spills in Galicia

A methodology is presented to investigate the recurrence of extraordinary events. The approach is fully general and complies with a canon of inference establishing a set of basic rationality requirements scientific reasoning should satisfy. In particular, we apply it to model the interarrival time between disastrous oil spills in the Galician coast in the northwest of Spain, one of the greatest risk areas in the world, as confirmed by the Prestige accident of November 2002. We formulate the problem within the logical probability framework, using plausible logic languages with observations to allow the appropriate expression of evidences. Therein, inference is regarded as the joint selection of a pair of reference and inferred probability distributions, which better encode the knowledge about potential times between incidents provided by the available evidences and other higher-order information at hand. To solve it, we employ the REF relative entropy method with fractile constraints. Next, we analyze the variability of the joint entropic solution, as knowledge that a time has elapsed since the last recorded spill is added, by conditioning the evidences. Attention is paid to the variability of two representative parameters: the average reference recurrence time and an inferred characteristic probability fractile for the time to an event. In contrast with classical results, the salient consequence is their nonconstancy with the elapsed time and the appearance of a variability pattern indicating an observational memory, even under the assumption of one-parameter exponential models, traditionally regarded as memoryless. Tanker accidentality is therefore dynamic, changing as time goes on with no further accidents. Generality of the methodology entails that identical conclusions would apply to hazard modeling of any other kind of extraordinary phenomena. This should be considered in risk assessment and management.     

Heteroscedastic log-exponentiated Weibull regression model

We introduce a new class of heteroscedastic log-exponentiated Weibull (LEW) regression models. The class of regression models can be applied to censored data and be used more effectively in survival analysis. Maximum likelihood estimation of the model parameters with censored data as well as influence diagnostics for the new regression model is investigated. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and compared to the performance of the heteroscedastic LEW regression model. The normal curvatures for studying local influence are derived under various perturbation schemes. An empirical application to a real data set is provided to illustrate the usefulness of the new class of heteroscedastic regression models.     

Types of Personal Social Networks of Older Adults in Portugal

This study presents and discusses a three-dimensional typology for personal social networks of Portuguese older adults. We used a K-means cluster analysis of structural, functional and relational-contextual variables of the networks of 612 participants aged 65?+?(M?=?76?±?7.6), mostly women (63%). Four types of networks emerged: family networks, friendship networks, neighbourhood networks and institutional networks. The most frequent are family networks (61.8%), constituted by 94.6% of family ties, on average, attesting the familistic nature of the older persons’ networks in Portugal, followed by friendship networks (23.5%) and neighbourhood networks (11.9%). The less frequent type is the institutional network (2.8%), dominated by formal ties (M?=?59.3%). Sociographic profiles reveal that family networks are more likely to be held by middle-old focal subjects, married or widowed, and with children. Friendship and neighbourhood networks are held by young-old subjects with different marital status, many of them living alone, with a higher proportion of men with friendship networks. Institutional networks are held by old–old, widowed or single with no children. The presented typology contributes to understand social support needs and social isolation. The conclusions allow to anticipate social services’ demand trajectories and to propose intervention plans and social policy measures to promote the wellbeing of the older population.

     

A cast of 40: population and family planning agencies at work in the Philippines

This is a compilation of 42 agencies, both government and private, participating in the Philippine population program. Each listing includes: the purpose of the organization; a summary of its activities for fiscal year 1974-1975; the name of the project director; and the address. A large number of these agencies are engaged primarily in population or family planning work. Others, such as the medical schools at the University of the Philippines and the University of Santo Tomas, have family planning programs as part of a broader effort.     

Estimation of distribution algorithms using Gaussian Bayesian networks to solve industrial optimization problems constrained by environment variables

Many real-world optimization problems involve two different subsets of variables: decision variables, and those variables which are not present in the cost function but constrain the solutions, and thus, must be considered during optimization. Thus, dependencies between and within both subsets of variables must be considered. In this paper, an estimation of distribution algorithm (EDA) is implemented to solve this type of complex optimization problems. A Gaussian Bayesian network is used to build an abstraction model of the search space in each iteration to identify patterns among the variables. As the algorithm is initialized from data, we introduce a new hyper-parameter to control the influence of the initial data in the decisions made during the EDA execution. The results show that our algorithm improves the cost function more than the expert knowledge does.