Data-driven stochastic inversion via functional quantization

In this paper, we propose a new methodology for solving stochastic inversion problems through computer experiments, the stochasticity being driven by a functional random variables. This study is motivated by an automotive application. In this context, the simulator code takes a double set of simulation inputs: deterministic control variables and functional uncertain variables. This framework is characterized by two features. The first one is the high computational cost of simulations. The second is that the probability distribution of the functional input is only known through a finite set of realizations. In our context, the inversion problem is formulated by considering the expectation over the functional random variable. We aim at solving this problem by evaluating the model on a design, whose adaptive construction combines the so-called stepwise uncertainty reduction methodology with a strategy for an efficient expectation estimation. Two greedy strategies are introduced to sequentially estimate the expectation over the functional uncertain variable by adaptively selecting curves from the initial set of realizations. Both of these strategies consider functional principal component analysis as a dimensionality reduction technique assuming that the realizations of the functional input are independent realizations of the same continuous stochastic process. The first strategy is based on a greedy approach for functional data-driven quantization, while the second one is linked to the notion of space-filling design. Functional PCA is used as an intermediate step. For each point of the design built in the reduced space, we select the corresponding curve from the sample of available curves, thus guaranteeing the robustness of the procedure to dimension reduction. The whole methodology is illustrated and calibrated on an analytical example. It is then applied on the automotive industrial test case where we aim at identifying the set of control parameters leading to meet the pollutant emission standards of a vehicle.     

On conditional risk estimation considering model risk

Usually, parametric procedures used for conditional variance modelling are associated with model risk. Model risk may affect the volatility and conditional value at risk estimation process either due to estimation or misspecification risks. Hence, non-parametric artificial intelligence models can be considered as alternative models given that they do not rely on an explicit form of the volatility. In this paper, we consider the least-squares support vector regression (LS-SVR), weighted LS-SVR and Fixed size LS-SVR models in order to handle the problem of conditional risk estimation taking into account issues of model risk. A simulation study and a real application show the performance of proposed volatility and VaR models.     

Population aging and long-term care policies in the Gulf region: a case study of Oman

Population aging is a phenomenon occurring across the globe including in countries traditionally exhibiting population dividends and “youth bulges.” The Gulf Corporation Council countries are no exception as they currently experience a process of population aging, albeit at a different stage from many developed countries. However, due to historically high fertility rates and fast-paced epidemiological transition, some of these countries will experience population aging at a higher pace than what has been observed in Europe and the United States. This article reviews recent developments in long-term care policies in the Gulf region with a focus on Oman as an example of a high-income Arab country that is experiencing population aging while still being governed by traditional family aged-care norms. Utilizing existing data and published research complemented by policy analysis and field visits, we analyze the process of population aging in Oman and neighboring countries and its policy implications.     

Patterns and severity of menopausal symptoms among Jordanian women

We examined 359 women aged 45–65 years who visited Jordan University Hospital between February and November 2014. The menopausal symptoms were assessed using a validated Arabic version of the menopause rating scale. The mean age at menopause was 49.4 years. Women aged 50–55 years more frequently exhibited hot flushes and vaginal dryness. Although premenopausal women were 1.5 times more likely to experience irritability, perimenopausal women were more likely to experience hot flushes, physical and mental irritability, sexual problems, vaginal dryness, and joint and muscular discomfort. Hence, health care providers should focus on women at all stages of life.     

Maximum likelihood approach to vote aggregation with variable probabilities

The Condorcet-Kemeny-Young statistical approach to vote aggregation is based on the assumption that voters have the same probability of comparing correctly two alternatives and that this probability is the same for any pair of alternatives. We relax the second part of this assumption by letting the probability of comparing correctly two alternatives be increasing with the distance between two alternatives in the allegedly true ranking. This leads to a rule in which the majority in favor of one alternative against another one is given a larger weight the larger the distance between the two alternatives in the true ranking, i.e., the larger the probability that the voters compare them correctly. This rule is not Condorcet consistent and does not satisfy local independence of irrelevant alternatives. Yet, it is anonymous, neutral, and paretian. It also appears that its performance in selecting the alternative most likely to be the best improves with the rate at which the probability increases.We would like to thank Michel Le Breton for his encouragement to examine this question and for his comments, as well as Philippe De Donder, Jean-Yves Duclos, Stephen Gordon, Cyril Téjédo and an anonymous referee for their comments.     

Expenditure Differences of University Degree Holders Across Occupational Sectors in Malaysia

This study was motivated by the key role university degree holders play in Malaysia's vision for the future and by concerns expressed about the drift of university degree holders from one sector to another. A questionnaire was mailed to a sample of 400 Malaysian families that had at least one member who held a university degree. The objective was to elicit details of the household economic situation of respondents, with special reference to the differences in expenditure patterns between families whose degree holder worked in higher education, government, or the private sector.Results of tobit analysis of expenditures show that there are some differences between the sectors regarding expenditure patterns, but the differences are not as great as expected. Nevertheless, university-educated persons in the private sector seem to have somewhat different expenditure patterns than their counterparts in other sectors.