TRACKING PRODUCT-PROCESS INTERACTIONS: A RESEARCH PARADIGM*

To design (or redesign) a competitive product, it is imperative that both the sales and manufacturing cost implications are assessed in a structured way. That is, the interactive (multidimensional) aspects of manufacturing and marketing variables need to be positioned in a proper perspective so that the system impact of variation in one or more variables may be ascertained quickly. In this paper we show how some of the system-related paradigms can be used as foundations for developing quantitative and qualitative models for tracking such interactive ímpacts. The emphasis is not on building complex mathematical models to solve specific problems but on providing a framework where system properties expressed as simple postulates can be used in an intelligent way to assess the impact of improvements in specific product-process scenarios.     

The Impact of Learning and Labor Attrition on Worker Flexibility in Dual Resource Constrained Job Shops

This study investigates the impact of worker learning, worker flexibility, and labor attrition on the system performance of a dual resource constrained (DRC) job-shop. The effects of learning and labor attrition have not been previously addressed in DRC literature. Results from the study, consistent with previous literature, show that the greatest benefits are achieved when inter-departmental worker flexibility is incrementally introduced into the system. In addition, the learning environment, which depends on the initial processing time of jobs and the learning rates of workers, is shown to impact the acquisition of flexibility. The study also shows that the impact of labor attrition on system performance under certain shop conditions may be significant.     

On hysteretic vector autoregressive model with applications

This paper proposes a new hysteretic vector autoregressive (HVAR) model in which the regime switching may be delayed when the hysteresis variable lies in a hysteresis zone. We integrate an adapted multivariate Student-t distribution from amending the scale mixtures of normal distributions. This HVAR model allows for a higher degree of flexibility in the degrees of freedom for each time series. We use the proposed model to test for a causal relationship between any two target time series. Using posterior odds ratios, we overcome the limitations of the classical approach to multiple testing. Both simulated and real examples herein help illustrate the suggested methods. We apply the proposed HVAR model to investigate the causal relationship between the quarterly growth rates of gross domestic product of United Kingdom and United States. Moreover, we check the pairwise lagged dependence of daily PM2.5 levels in three districts of Taipei.     

Estimation of the intensity function of an inhomogeneous Poisson process with a change‐point

Recent work on point processes includes studying posterior convergence rates of estimating a continuous intensity function. In this article, convergence rates for estimating the intensity function and change‐point are derived for the more general case of a piecewise continuous intensity function. We study the problem of estimating the intensity function of an inhomogeneous Poisson process with a change‐point using non‐parametric Bayesian methods. An Markov Chain Monte Carlo (MCMC) algorithm is proposed to obtain estimates of the intensity function and the change‐point which is illustrated using simulation studies and applications. The Canadian Journal of Statistics 47: 604–618; 2019 © 2019 Statistical Society of Canada     

Confidence intervals based on the deviance statistic for the hyperparameters in state space models

The main objective of this work is to evaluate the performance of confidence intervals, built using the deviance statistic, for the hyperparameters of state space models. The first procedure is a marginal approximation to confidence regions, based on the likelihood test, and the second one is based on the signed root deviance profile. Those methods are computationally efficient and are not affected by problems such as intervals with limits outside the parameter space, which can be the case when the focus is on the variances of the errors. The procedures are compared to the usual approaches existing in the literature, which includes the method based on the asymptotic distribution of the maximum likelihood estimator, as well as bootstrap confidence intervals. The comparison is performed via a Monte Carlo study, in order to establish empirically the advantages and disadvantages of each method. The results show that the methods based on the deviance statistic possess a better coverage rate than the asymptotic and bootstrap procedures.     

Recent developments in D-optimal designs

In the paper, some issues concerned with the determining spring balance weighing designs satisfying the criterion of D-optimality under the assumption measurement errors are uncorrelated and they have the same variances are discussed. In addition, highly D-efficient spring balance weighing designs are also considered. Some conditions under which any spring balance weighing design is regular D-optimal or highly D-efficient are proved. What is more, new construction methods of regular D-optimal and highly D-efficient spring balance weighing designs are presented.     

A reflected feature space for CART

We present an algorithm for learning oblique decision trees, called HHCART(G). Our decision tree combines learning concepts from two classification trees, HHCART and Geometric Decision Tree (GDT). HHCART(G) is a simplified HHCART algorithm that uses linear structure in the training examples, captured by a modified GDT angle bisector, to define splitting directions. At each node, we reflect the training examples with respect to the modified angle bisector to align this linear structure with the coordinate axes. Searching axis parallel splits in this reflected feature space provides an efficient and effective way of finding oblique splits in the original feature space. Our method is much simpler than HHCART because it only considers one reflected feature space for node splitting. HHCART considers multiple reflected feature spaces for node splitting making it more computationally intensive to build. Experimental results show that HHCART(G) is an effective classifier, producing compact trees with similar or better results than several other decision trees, including GDT and HHCART trees.     

Special issue dedicated to Odd O. Aalen

Lifetime Data Analysis -     

Transnational queer sociological analysis of sexual identity and civic‐political activism in Hong Kong,Taiwan and mainland China

The sociology of homosexuality lacks engagement with queer theory and postcolonialism and focuses primarily on the global metropoles, thus failing to provide a plausible account of non‐Western non‐normative sexual identities. This research adopts the author’s newly proposed transnational queer sociology to address these deficiencies. First, it critiques the Western model of sexual identity predominantly employed to elucidate non‐Western, non‐normative sexualities. It does so by examining not only the queer flows between West and non‐West but also those among and within non‐Western contexts to produce translocally shared and mutually referenced experiences. Second, the proposed approach combines sociology with queer theory by emphasizing the significant role of material, as well as discursive, analyses in shaping queer identities, desires and practices. This article employs the approach to examine young gay male identities, as revealed in 90 in‐depth interviews conducted in Hong Kong (n = 30), Taiwan (Taipei, n = 30) and mainland China (Shanghai, n = 30) between 2017 and 2019. More specifically, it highlights the interplay between the state and identity by investigating the intersection and intertwining effects of these young men’s sexual and cultural/national identities, revealing three different forms of civic‐political activism. The article both demonstrates the way in which sexuality and the state are mutually constituted and provides nuanced analysis of the heterogeneity of contemporary homosexualities in Hong Kong, Taiwan and mainland China. In applying a new sociological approach to understanding sexuality, this research joins the growing body of scholarship within sociology that is decentring the Western formation of universal knowledge.     

Protecting and Benchmarking Migrants’ Rights: An Analysis of the Global Compact for Safe,Orderly and Regular Migration

The Global Compact for Safe, Orderly, and Regular Migration (GCM) was to be “guided by human rights law and standards” in recognition of the rights of international migrants, who are currently protected by an overlapping patchwork of treaties and international law. The GCM contains many laudable commitments that, if implemented, will ensure that states more consistently respect, protect, and fulfil the rights of all migrants and also that states incorporate data on migration into a more cohesive governance regime that does more to promote cooperation on the issue of international migration. However, many concerns remain. Using a legal analysis and cross‐national policy data, we find that the GCM neither fully articulates existing law nor makes use of international consensus to expand the rights of migrants. In its first section, this article provides a concise analysis of the GCM's compliance with a set of core principles of existing international human rights law regarding migrants. In the second section, we apply a novel instrument to create an objective, cross‐national accounting of the laws protecting migrants’ rights in various national legal frameworks. Focusing on a sample of five diverse destination and sending countries, the results suggest we are close to an international consensus on the protection of a core set of migrants’ rights. This analysis should help prioritize the work necessary to implement the GCM.