Skewness Reduction Approach in Multi-Attribute Process Monitoring

Since the product quality of many industrial processes depends upon more than one dependent variable or attribute, they are either multivariate or multi-attribute in nature. Although multivariate statistical process control is receiving increased attention in the literature, little work has been done to deal with multi-attribute processes. In this article, we develop a new methodology to monitor multi-attribute processes. To do this, first we transform multi-attribute data in a way that their marginal probability distributions have almost zero skewness. Then, we estimate the transformed covariance matrix and apply the well-known T ² control chart. In order to illustrate the proposed method and evaluate its performance, we use two simulation experiments and compare the results with the ones from both MNP chart and the χ² control chart.     

A superiority problem in misspecified restricted linear models

Abstract

In this article we study the relationship between principal component analysis and a multivariate dependency measure. It is shown, via simulated examples and real data, that the information provided by principal components is compatible with that obtained via the dependency measure δ. Furthermore, we show that in some instances in which principal component analysis fails to give reasonable results due to nonlinearity among the random variables, the dependency statistic δ still provides good results. Finally, we give some ideas about using the statistic δ in order to reduce the dimensionality of a given data set.     

Robust estimation of the correlation matrix of longitudinal data

We propose a double-robust procedure for modeling the correlation matrix of a longitudinal dataset. It is based on an alternative Cholesky decomposition of the form Σ=DLL ^? D where D is a diagonal matrix proportional to the square roots of the diagonal entries of Σ and L is a unit lower-triangular matrix determining solely the correlation matrix. The first robustness is with respect to model misspecification for the innovation variances in D, and the second is robustness to outliers in the data. The latter is handled using heavy-tailed multivariate t-distributions with unknown degrees of freedom. We develop a Fisher scoring algorithm for computing the maximum likelihood estimator of the parameters when the nonredundant and unconstrained entries of (L,D) are modeled parsimoniously using covariates. We compare our results with those based on the modified Cholesky decomposition of the form LD ² L ^? using simulations and a real dataset.     

A note on optimal price,warranty length and production rate for free replacement policy in static demand markets

This note provides some extensions on optimal policies on price, warranty length and production rate proposed by Wu et al. (2009) [1] (Wu, C.C.; Chou, C.Y.; Huang C. Optimal price, warranty length and production rate for free replacement policy in the static demand market. Omega 2009; 37: 29–39.) More specifically, the assumptions of the original paper is extended in this note from the production rate being positive and the second derivative of the demand function with respect to price and warranty-length being negative to no restrictions on both.     

An investigation of mental health and personality in Swedish social work students upon entry to university training

The aims were to describe Swedish social work students' personality characteristics upon entry to their training and to analyze relationships between personality traits, mental health, and some sociodemographic variables. One hundred and twenty-one female social work students completed a sociodemographic form, the Temperament and Character Inventory, and the Symptom Checklist. They scored significantly higher on harm avoidance, reward dependence, and self-transcendence and reported more somatization, obsessive compulsive, and phobic-anxious symptoms, and less hostility, than Swedish individuals from the general population of the same age. Personality traits significantly predicted the various mental symptom scores. It is recommended to implement modules or training courses within social work training in Sweden that bring an improvement of self-directedness and cooperativeness character trait into focus.     

YOUTH,REVOLUTION, AND REPRESSION

We develop a simple model to study the effect of age structure on the interactions between the state and dissidents. Younger populations are more prone to protest. As the population grows younger, states that can discriminately target repression to different groups, but cannot concede discriminately, decrease repression. In contrast, states that can target concession, but not repression, increase repression. We test these results in nonmilitary single‐party regimes and military regimes without political parties. Moreover, we study state response to dissent in East European communist regimes in the late 1980s, showing that state response was more repressive in countries with younger populations. (JEL D74)     

Investment Areas to Enhance Public Employee Resilience during the Coronavirus Disease 2019 (COVID-19): Evidence from Iran

Public Organization Review - This study aims to investigate the areas of investment that the human resources management of the Iranian public sector has invested in for improving employees'...     

HIV prevention barriers in transgender women: a qualitative study

Abstract

Sexual contact is still one of the most important routes of HIV transmission. The aim of this study was identify the factors that underlie the higher prevalence of high-risk sexual behaviors in a sample of transgender women in Iran. The qualitative study used face-to-face, semi-structured, in-depth interviews in a sample of 15 transgender women. Our participants used sexual practices as a way to be approved/accepted as a woman. Using sex for this purpose led them to engage in high-risk sexual relationships. It is essential to consider these issues in consulting and education about high-risk behaviors.     

A faster strongly polynomial time algorithm to solve the minimum cost tension problem

This paper presents a strongly polynomial time algorithm for the minimum cost tension problem, which runs in \(O(\max \{m^3n, m^2 \log n(m+n \log n)\})\) time, where n and m denote the number of nodes and number of arcs, respectively. Our algorithm improves upon the previous strongly polynomial time of \(O(n^4 m^3 \log n)\) due to Hadjiat and Maurras (Discret Math 165(166):377–394, 1997).