Robust Estimation of Parameters in Simple Linear Profiles Using M-Estimators

In many situations, the quality of a process or product may be better characterized and summarized by a relationship between the response variable and one or more explanatory variables. Parameter estimation is the first step in constructing control charts. Outliers may hamper proper classical estimators and lead to incorrect conclusions. To remedy the problem of outliers, robust methods have been developed recently. In this article, a robust method is introduced for estimating the parameters of simple linear profiles. Two weight functions, Huber and Bisquare, are applied in the estimation algorithm. In addition, a method for robust estimation of the error terms variance is proposed. Simulation studies are done to investigate and evaluate the performance of the proposed estimator, as well as the classical one, in the presence and absence of outliers under different scenarios by the means of MSE criterion. The results reveal that the robust estimators proposed in this research perform as well as classical estimators in the absence of outliers and even considerably better when outliers exist. The maximum value of variance estimate in one scenario obtained from classical estimator is 10.9, while this value is 1.66 and 1.27 from proposed robust estimators when its actual value is 1.     

Gender as a Moderator of the Relation Among Social Support Functions and Life Satisfaction in Older Malaysians

The aim of this study was to examine the moderating role of gender on relations among social support functions and life satisfaction in older Malaysians. The study sample was 1,800 older residents in a community; all were at least 60 years old. This study was a cross-sectional and corelational survey, and the data were collected by multistage stratified sampling. This study revealed that fewer social support functions, and therefore less life satisfaction, were available for females than for males. The results of moderated regression analyses demonstrated that gender interacted only on the relationship between positive social interaction support and tangible support with life satisfaction. Specifically, at a high tangible support level, females had lower life satisfaction when compared to a low tangible support level. There may be a need for new programs and services to provide other aspects of social support to older female adults to improve and maintain life satisfaction in later life.     

High dimensional extension of the growth curve model and its application in genetics

Recent advances in technology have allowed researchers to collect large scale complex biological data, simultaneously, often in matrix format. In genomic studies, for instance, measurements from tens to hundreds of thousands of genes are taken from individuals across several experimental groups. In time course microarray experiments, gene expression is measured at several time points for each individual across the whole genome resulting in a high-dimensional matrix for each gene. In such experiments, researchers are faced with high-dimensional longitudinal data. Unfortunately, traditional methods for longitudinal data are not appropriate for high-dimensional situations. In this paper, we use the growth curve model and introduce test useful for high-dimensional longitudinal data and evaluate its performance using simulations. We also show how our approach can be used to filter genes in time course genomic experiments. We illustrate this using publicly available genomic data, involving experiments comparing normal human lung tissue with vanadium pentoxide treated human lung tissue, designed with the aim of understanding the susceptibility of individuals working in petro-chemical factories to airway re-modelling. Using our method, we were able to filter out 1053 (about 5 %) genes as non-noise genes from a pool of  22,277. Although our focus is on hypothesis testing, we also provided modified maximum likelihood estimator for the mean parameter of the growth curve model and assessed its performance through bias and mean squared error.     

Homogeneity test based on ranked set samples

Abstract

The homogeneity hypothesis is investigated in a location family of distributions. A moment-based test is introduced based on data collected from a ranked set sampling scheme. The asymptotic distribution of the proposed test statistic is determined and the performance of the test is studied via simulation. Furthermore, for small sample sizes, the bootstrap procedure is used to distinguish the homogeneity of data. An illustrative example is also presented to explain the proposed procedures in this paper.     

Team selection for prediction tasks

Given a random variable \(O \in \mathbb {R}\) and a set of experts \(E\), we describe a method for finding a subset of experts \(S \subseteq E\) whose aggregated opinion best predicts the outcome of \(O\). Therefore, the problem can be regarded as a team formation for performing a prediction task. We show that in case of aggregating experts’ opinions by simple averaging, finding the best team (the team with the lowest total error during past \(k\) rounds) can be modeled with an integer quadratic programming and we prove its NP-hardness whereas its relaxation is solvable in polynomial time. At the end, we do an experimental comparison between different rounding and greedy heuristics on artificial datasets which are generated based on calibration and informativeness of exprets’ information and show that our suggested tabu search works effectively.     

Integration of process planning and production planning and control in cellular manufacturing

Organisations willing to succeed in global competition have to integrate their internal and external processes. This especially includes planning and production control (PPC) processes. Optimised allocation of the production resources and quick response to demand changes result in lower cost and improvement of production performance. Practitioners and researchers have been trying to achieve these goals using production planning techniques. Although the results are significant, it seems necessary to integrate production operations in order to improve the production performance. The goals, information and decisions taken in production planning and control and process planning are often very different and difficult to integrate in Cellular Manufacturing (CM) environments. Designing an efficient PPC system and integrating it with process planning in a cellular environment is of the same importance. The following paper proposes first a comprehensive framework of integrated process planning and production planning and control in CM. Then, with respect to this framework and utilising the domain knowledge in the area of CM systems, an integrated model based on Integrated Definition Modeling Language is developed. The application of the models has been considered as a case study for a production system in electronics and telecommunication sector in a plant in Iran. The validity and completeness of the proposed model is tested by a panel of experts in the areas of production planning and control in CM environments.     

Risk‐Mitigating Policies and Adversarial Behavior: Case of Backlash

A probabilistic game‐theoretic model is developed within both a static and a dynamic framework to capture adversary–defender conflict in the presence of backlash. I find that not accounting for backlash in counteradversary policies may be costly to the target government. But to minimize adversarial backlash requires understanding how backlash emerges and if, and how, adversaries strategize to goad target governments into policies that induce backlash. The dynamic version of the model shows that when backlash occurs with a time lag, an escalation of the conflict is likely to occur.     

Herding and Contrarian Behavior in Financial Markets

Rational herd behavior and informationally efficient security prices have long been considered to be mutually exclusive but for exceptional cases. In this paper we describe the conditions on the underlying information structure that are necessary and sufficient for informational herding and contrarianism. In a standard sequential security trading model, subject to sufficient noise trading, people herd if and only if, loosely, their information is sufficiently dispersed so that they consider extreme outcomes more likely than moderate ones. Likewise, people act as contrarians if and only if their information leads them to concentrate on middle values. Both herding and contrarianism generate more volatile prices, and they lower liquidity. They are also resilient phenomena, although by themselves herding trades are self‐enforcing whereas contrarian trades are self‐defeating. We complete the characterization by providing conditions for the absence of herding and contrarianism.     

Keynes's grandchildren and Marx's gig workers: Why human labour still matters

The current anxiety around the globe regarding automation and “the future of work”, the irrelevance of human labour and the superfluity of humans is based on recurring ideas about technology, work and economic value. Not quite novel, the debate on these ideas dates back to prominent thinkers, such as Karl Marx and John Maynard Keynes. To grasp the present moment, therefore, the authors revisit this debate within the broader history of capitalism. With a focus on labour and technology, they bring attention to the hidden forms of value creation in the current economy and to the blind spots of the historical debate, and envision various possible scenarios for the future.