Estimates of fertility in Bangladesh

The attempt is made to estimate fertility levels in Bangladesh on the basis of data collected during the 1974 Census. In the 1st section attention is directed to providing an overall picture of the demographic situation in the country. Comparisons between the 1961 and 1974 data demonstrates that the 1974 Census data provide consistent results. Factors such as the degree of urbanization, literacy and economic participation rates--considered as indicators of development--all seem to show little progress during the intercensal period. The use of child/women ratios (CWRs) provides plausible evidence of the likelihood of a fertility decline. A decline in CWR values is small for "all areas" but a marked decline can be noted for "urban areas." The recorded mean number of children is less in 1974 than in 1961 for women under age 35 whereas for the older groups the 1974 Census shows higher mean numbers. The Bangladesh Fertility Survey (BFS) data result for the total fertility rate of 6.58 is very close to that estimated for the 1974 Census--6.59. The reverse survival method also indicates that birthrates have been lower during the 1969-1974 period.     

Selecting a Good Stochastic System for the Large Number of Alternatives

In this article, we present the problem of selecting a good stochastic system with high probability and minimum total simulation cost when the number of alternatives is very large. We propose a sequential approach that starts with the Ordinal Optimization procedure to select a subset that overlaps with the set of the actual best m% systems with high probability. Then we use Optimal Computing Budget Allocation to allocate the available computing budget in a way that maximizes the Probability of Correct Selection. This is followed by a Subset Selection procedure to get a smaller subset that contains the best system among the subset that is selected before. Finally, the Indifference-Zone procedure is used to select the best system among the survivors in the previous stage. The numerical test involved with all these procedures shows the results for selecting a good stochastic system with high probability and a minimum number of simulation samples, when the number of alternatives is large. The results also show that the proposed approach is able to identify a good system in a very short simulation time.     

Selective Maintenance in System Reliability with Random Costs of Repairing and Replacing the Components

In this paper we consider the problem of determining the optimum number of repairable and replaceable components to maximize a system's reliability when both, the cost of repairing the components and the cost of replacement of components by new ones, are random. We formulate it as a problem of non-linear stochastic programming. The solution is obtained through Chance Constrained programming. We also consider the problem of finding the optimal maintenance cost for a given reliability requirement of the system. The solution is then obtained by using Modified E-model. A numerical example is solved for both the formulations.     

An empirical study of the type I error rate and power for some selected normal-theory and nonparametric tests of the independence of two sets of variables

Normal-theory tests of the hypothesis of no relationship among two sets of variables require assumptions of independence, hamoscedasticity, and normality. If, however, the assumption of normality is not tenable, there are few guidelines for properly using these tests. Historically, the lack of a comprehensive hypothesis-testing framework in the nonparametric case has provided few alternatives to normal-theory procedures. Fortunately, this situation has changed with the introduction of nonparametric, general linear model-based tests that can be used with existing computing packages. Multivariate-nonparametric tests due to Puri and Sen (1969, 1971, 1985) and Conover and Iman (1981) are outlined, and the results of a simulation study of the performance of three nonparametric and one normal-theory test of the hypothesis of no relationship among two sets of variables are presented. These results suggest that multivariate-nonparametric tests should be considered for a variety of data conditions. especially heavy-tailed and badly skewed data for small samples and a large number of variates.     

Some aspects of probability forecasting

The problems of assessing, comparing and combining probability forecasts for a binary events sequence are considered. A Gaussian threshold model (analytically of closed form) is introduced which allows generation of different probability forecast sequences valid for the same events. Chi - squared type test statistics, and also a marginal-conditional method are proposed for the assessment problem, and an asymptotic normality result is given. A graphical method is developed for the comparison problem, based upon decomposing arbitrary proper scoring rules into certain elementary scoring functions. The special role of the logarithmic scoring rule is examined in the context of Neyman - Pearson theory.     

On E-Bayesian estimations for the cumulative hazard rate and mean residual life under generalized inverted exponential distribution and type-II censoring

Estimation of reliability and hazard rate is necessary in many applications. To this aim, different methods of estimation have been employed. Each method suffers from its own problems such as complexity of calculations, high risk and so on. Toward this end, this study employed a new method, E-Bayesian, for estimating the parametric functions of the Generalized Inverted Exponential distribution, which is one of the most noticeable distributions in lifetime studies. Relations are derived under a squared error loss function, type-II censoring and a conjugate prior. E-Bayesian estimations are obtained based on different priors of the hyperparameters to investigate the influence of different prior distributions on these estimations. The asymptotic behaviors of E-Bayesian estimations and relations among them have been investigated. Finally, a comparison among the maximum likelihood, Bayes and E-Bayesian estimations in different sample sizes are made, using a real data and the Monte Carlo simulation. Simulations show that the new presented method is more efficient than previous methods and is also easy to operate. Also, some comparisons among the results of Generalized Inverted Exponential distribution, Exponential distribution and Generalized Exponential distribution are provided.KEYWORDS: E-Bayesian estimation, generalized Inverted exponential distribution, type-II censoring, reliability, hazard rate, Monte Carlo simulation     

Multivariate process dispersion monitoring without subgrouping

The memory-type adaptive and non-adaptive control charts are among the best control charts for detecting small-to-moderate changes in the process parameter(s). In this paper, we propose the Crosier CUSUM (CCUSUM), EWMA, adaptive CCUSUM (ACCUSUM) and adaptive EWMA (AEWMA) charts for efficiently monitoring the changes in the covariance matrix of a multivariate normal process without subgrouping. Using extensive Monte Carlo simulations, the length characteristics of these control charts are computed. It turns out that the ACCUSUM and AEWMA charts perform uniformly and substantially better than the CCUSUM and EWMA charts when detecting a range of shift sizes in the covariance matrix. Moreover, the AEWMA chart outperforms the ACCUSUM chart. A real dataset is used to explain the implementation of the proposed control charts.     

A semiparametric approach for modelling multivariate nonlinear time series

In this article, a semiparametric time‐varying nonlinear vector autoregressive (NVAR) model is proposed to model nonlinear vector time series data. We consider a combination of parametric and nonparametric estimation approaches to estimate the NVAR function for both independent and dependent errors. We use the multivariate Taylor series expansion of the link function up to the second order which has a parametric framework as a representation of the nonlinear vector regression function. After the unknown parameters are estimated by the maximum likelihood estimation procedure, the obtained NVAR function is adjusted by a nonparametric diagonal matrix, where the proposed adjusted matrix is estimated by the nonparametric kernel estimator. The asymptotic consistency properties of the proposed estimators are established. Simulation studies are conducted to evaluate the performance of the proposed semiparametric method. A real data example on short‐run interest rates and long‐run interest rates of United States Treasury securities is analyzed to demonstrate the application of the proposed approach. The Canadian Journal of Statistics 47: 668–687; 2019 © 2019 Statistical Society of Canada     

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.     

Women–Family in Quality Perspective

Bringing together women and family in quality perspective bring about interesting discussions in this paper. By integrating previous studies and considering expert opinions, we determinate the variables and dimensions with respect to women’s existence regarding their roles both in the family and at work. Many activities carried out by women represent the consumer aspects of their role. Women undertake these activities to fulfill their needs, which can be classified in the order of preference using Maslow’s Hierarchy of Need. Women success can be measured based on their ability to perform their roles successfully. We identify women’s performance by using quality approach of Personal Quality Maintenance (PQM), which is widely applied in many organizations in order to maintain the service delivery, which meets the customer satisfaction. The effort to enhance women’s satisfaction for their success in playing the multirole in the family and at work is our main consideration. This study may contribute a new point of view regarding for the women’s welfare and existence.