Robust estimation in the generalized poisson model

A computationally simple method of robust estimation in the generalized Poisson model is presented. Estimators are proved to be optimal in the sense of local minimax testing, conditionally on the explanatory variable. Results of a Monte Carlo experiment are supplemented where robust and efficient estimators are compared.     

Online Control Charts for Process Averages Based on Repeated Median Filters

Two types of estimates of process level, namely repeated median estimates (Siegel, 1982 Siegel , A. F. ( 1982 ). Robust regression using repeated medians . Biometrika 69 : 242 – 244 .[Crossref], [Web of Science ®] , [Google Scholar]) and full online estimates (Gather et al., 2006 Gather , U. , Schettlinger , K. , Fried , R. ( 2006 ). Online signal extraction by robust linear regression . Computational Statistics 21 : 33 – 51 .[Crossref], [Web of Science ®] , [Google Scholar]) based on repeated median filters, are used to develop control charts. The distributional properties of the estimates are studied using simulation and these are found to closely follow normal distribution. The repeated median being robust against outliers with asymptotically 50% breakdown value and having small standard deviation is found to be useful as a basis for monitoring process averages. The control charts using repeated median estimates have been recommended for general use.     

Number of Replications Required in Control Chart Monte Carlo Simulation Studies

Monte Carlo simulations have been used extensively in studying the performance of control charts. Researchers have used various numbers of replications in their studies, but almost none of them provided justifications for the number of replications used. Currently, there are no empirically based recommendations regarding the required number of replications to ensure accurate results. This research examined six recently published studies to develop recommendations for the minimum number of replications necessary to reproduce the reported results within a specified degree of accuracy. The results of this study indicated that using 10,000 replications was unnecessarily large and a smaller number of replications could be used to reproduce the target ARLs within the 2% error bands satisfying the modified Mundfrom's criteria. In many cases, only 5,000 replications or fewer were required. In general, the number of replications required to reproduce the target ARL decreased as the shift size increased. In addition, the results of this study provide general recommendations for the required number of replications to use in future SPC simulation studies.     

Alternative Factors for Control Chart Construction

Conflicting decision signals resulting from Shewhart Mean and Variability Control Charts produce undesirable consequences. Therefore, we construct “six-sigma” control charts by alternative methods to avoid problems associated with Control Charts yielding different signals. By adjusting methods for control chart construction for dispersion charts, we produce new reference tables. The new tables provide consistent signals and appear similar and familiar to users of historical tables.     

The Optimal Allocation Combination for the One-Sided Sequential Screening Procedure Based on the Individual Misclassification Error

In this article, the expected total costs of three kinds of quality cost functions for the one-sided sequential screening procedure based on the individual misclassification error are obtained, where the expected total cost is the sum of the expected cost of inspection, the expected cost of rejection, and the expected cost of quality. The computational formulas for three kinds of expected total costs are derived when k screening variables are allocated into r stages. The optimal allocation combination is determined based on the criterion of minimum expected total cost. At last, we give one example to illustrate the selection of the optimal allocation combination for the sequential screening procedure.     

Technology as a Weapon in Domestic Violence: Responding to Digital Coercive Control

ABSTRACT

Technology-facilitated domestic violence is an emerging issue for social workers and other service providers. The concept of Digital Coercive Control (DCC) is introduced to highlight the particular nature and impacts of technology-facilitated abuse in the context of domestic violence. While practitioners have become more adept at working with women experiencing DCC, there is still little known about its dynamics and whether this violence requires a change in current service responses. This article explores findings from survey research conducted with 546 Australian domestic violence practitioners about the ways perpetrators use technology as part of their abuse tactics. The findings demonstrate that DV practitioners believe perpetrator use of technology is extensive and has significant impacts on the safety of clients. A major dilemma faced by practitioners is how to promote and facilitate client safety from DCC while still enabling safe use of technology so clients can remain connected to family, friends, and community.

IMPLICATIONS

• The use of digital technology in domestic violence creates a significant practice issue for Australian domestic violence practitioners.

• The development of a practice framework for responding to digital coercive control may assist practitioners to highlight the risks posed by this abuse, while still enabling women and children the freedom to participate in the digital realm.

     

A neuroeconomic theory of (dis) honesty

We develop a theory of dishonesty based on neurophysiological evidence that supports the idea of a two-step process in the decision to cheat. Formally, decisions can be processed vía a costless “honest” channel that generates truthful behavior or vía a costly “dishonest” channel that requires attentional resources to trade-off costs and benefits of cheating. In the first step, a decision between these two channels is made based on ex-ante information regarding the expected benefits of cheating. In the second step, decisions are based on the channel that has been selected and, when applicable, the realized benefit of cheating. The model makes novel predictions relative to existing behavioral theories. First, adding external complexity to the decision-making problem (e.g., in the form of multi-tasking) deprives the individual from attentional resources and consequently decreases the propensity to engage in dishonest behavior. Second, higher expectations about the benefits of cheating results in a higher frequency of trial-by-trial cheating for any realized benefit level. Third, multiplicity of equilibria (characterized by different levels of cheating) emerges naturally in the context of illegal markets, in which expected benefits are endogenous.     

Another Remark on the Alternative Expectation Formula

Students in a calculus-based probability course will often see the expectation formula for nonnegative continuous random variables in terms of the survival function. This alternative expectation formula has a wide spectrum of applications. It is natural to ask whether there is a multivariate version of this formula. This note gives an affirmative answer by establishing such a formula using two different approaches. The two approaches employed in this note correspond to the two approaches for the univariate case. Supplementary materials for this article are available online.