On the mean residual life of records

Suppose that a technical system is subject to shocks, e.g. peaks of voltages from a sequence of identically independent voltages having a lower limit value v>0$v>0$. We propose a new definition for the mean residual life of the records of the sequence and study its various properties.     

Risk Management in a Polio-Free World

Inherent in the decision to launch the Global Polio Eradication Initiative in 1988 was the expectation for many people that immunization against poliomyelitis would eventually simply stop, as had been the case with smallpox following its eradication in 1977. However, the strategies for managing the risks associated with a "polio-free" world must be continuously refined to reflect new developments, particularly in our understanding of the live polioviruses in the oral poliovirus vaccine (OPV) and in the international approach to managing potential biohazards. The most important of these developments has been the confirmation in 2000 that vaccine-derived polioviruses (VDPVs) can circulate and cause polio outbreaks, making the use of OPV after interruption of wild poliovirus transmission incompatible with a polio-free world. A comprehensive strategy has been developed to minimize the risks associated with eventual OPV cessation, centered on appropriate long-term biocontainment of poliovirus stocks (whether for vaccine production, diagnosis, or research), the controlled reintroduction of any live poliovirus vaccine (i.e., from an OPV stockpile), and appropriate use of the inactivated poliovirus vaccine (IPV). Although some aspects of this risk management strategy are still debated, there is wide agreement that no strategy would entirely eliminate the potential risks to a polio-free world. The current strategy for risk management in a polio-free world will continue to evolve with better characterization of these risks and the development of more effective approaches both to reduce those risks and to limit their consequences should they occur.     

Determinants of Infant Mortality in Older ASEAN Economies

Infant mortality in the Association of Southeast Asian Nations (ASEAN) has been declining, yet disparities remain between the nations. This paper therefore explores the determinants of infant mortality in the older ASEAN-4 economies, Malaysia, Thailand, Indonesia and the Philippines using an Autoregressive Distributed Lag (ARDL) Error Correction Model framework. The key findings of the study are: First, there is evidence of long-run relationships among infant mortality, education, female fertility, income and access to healthcare. Second, the determinants of infant mortality vary between countries. Female fertility emerged as the main determinant of infant mortality in Malaysia, while access to healthcare matter for infant mortality in Indonesia, and to a lesser extent for the Philippines. The income effect is significant for reducing infant mortality in Malaysia, while female education is important for Indonesia and Thailand. Third, the speed of adjustment of infant mortality rate is comparatively low in ASEAN-4.     

On the $$L_p$$ norms of kernel regression estimators for incomplete data with applications to classification

We consider kernel methods to construct nonparametric estimators of a regression function based on incomplete data. To tackle the presence of incomplete covariates, we employ Horvitz–Thompson-type inverse weighting techniques, where the weights are the selection probabilities. The unknown selection probabilities are themselves estimated using (1) kernel regression, when the functional form of these probabilities are completely unknown, and (2) the least-squares method, when the selection probabilities belong to a known class of candidate functions. To assess the overall performance of the proposed estimators, we establish exponential upper bounds on the \(L_p\) norms, \(1\le p<\infty \), of our estimators; these bounds immediately yield various strong convergence results. We also apply our results to deal with the important problem of statistical classification with partially observed covariates.     

Computational approach test for inference about several correlation coefficients: Equality and common

In this article, we consider inference about the correlation coefficients of several bivariate normal distributions. We first propose computational approach tests for testing the equality of the correlation coefficients. In fact, these approaches are parametric bootstrap tests, and simulation studies show that they perform very satisfactory, and the actual sizes of these tests are better than other existing approaches. We also present a computational approach test and a parametric bootstrap confidence interval for inference about the parameter of common correlation coefficient. At the end, all the approaches are illustrated using two real examples.     

The McDonald Gompertz distribution: Properties and applications

This article introduces a five-parameter lifetime model called the McDonald Gompertz (McG) distribution to extend the Gompertz, generalized Gompertz, generalized exponential, beta Gompertz, and Kumaraswamy Gompertz distributions among several other models. The hazard function of new distribution can be increasing, decreasing, upside-down bathtub, and bathtub shaped. We obtain several properties of the McG distribution including moments, entropies, quantile, and generating functions. We provide the density function of the order statistics and their moments. The parameter estimation is based on the usual maximum likelihood approach. We also provide the observed information matrix and discuss inferences issues. The flexibility and usefulness of the new distribution are illustrated by means of application to two real datasets.     

Optimal acceptance sampling policy considering Bayesian risks

In this paper, we propose a sampling policy considering Bayesian risks. Various definitions of producer's risk and consumer's risk have been made. Bayesian risks for both producer and consumer are proven to give better information to decision-makers than classical definitions of the risks. So considering the Bayesian risk constraints, we seek to find optimal acceptance sampling policy by minimizing total cost, including the cost of rejecting the batch, the cost of inspection, and the cost of defective items detected during the operation. Proper distributions to construct the objective function of the model are specified. In order to demonstrate the application of the proposed model, we illustrate a numerical example. Furthermore, the results of the sensitivity analysis show that lot size, the cost of inspection, and the cost of one defective item are key factors in sampling policies. The acceptable quality level, the lot tolerance proportion defective, and Bayesian risks also affect the sampling policy, but variations of acceptable quality level and producer Bayesian risks, for values more than a specified value, cause no changes in sampling policy.     

How the acculturation of Baba Nyonya community affects Malacca food identity?

ABSTRACT

The migration of the Chinese community to Malacca in the 16th century has enabled the process of cross culturing and culinary acculturation, producing a unique mixture of Baba Nyonya food. Even though Baba Nyonya food is pretty much has been localised (Malay), its Chinese representation cannot be denied. This study aims to assess how the acculturation of the Baba Nyonya community affects Malacca food identity. A quantitative methodology is employed in this study. This study classifies Baba Nyonya food acculturation through (1) types of food; (2) methods of cooking; (3) ingredients; and (4) eating decorum. From the regression analysis, this study found that Baba Nyonya cultural polarity explains significant variation in the formation of Malacca food identity. This study then elaborates on the importance of Baba Nyonya food in Malacca destination branding.     

Skew-mixed effects model for multivariate longitudinal data with categorical outcomes and missingness

A longitudinal study commonly follows a set of variables, measured for each individual repeatedly over time, and usually suffers from incomplete data problem. A common approach for dealing with longitudinal categorical responses is to use the Generalized Linear Mixed Model (GLMM). This model induces the potential relation between response variables over time via a vector of random effects, assumed to be shared parameters in the non-ignorable missing mechanism. Most GLMMs assume that the random-effects parameters follow a normal or symmetric distribution and this leads to serious problems in real applications. In this paper, we propose GLMMs for the analysis of incomplete multivariate longitudinal categorical responses with a non-ignorable missing mechanism based on a shared parameter framework with the less restrictive assumption of skew-normality for the random effects. These models may contain incomplete data with monotone and non-monotone missing patterns. The performance of the model is evaluated using simulation studies and a well-known longitudinal data set extracted from a fluvoxamine trial is analyzed to determine the profile of fluvoxamine in ambulatory clinical psychiatric practice.