A characterization of majority voting rules with quorums

We give a characterization of majority voting rules with quorums in the framework of May (Econometrica 20:680–684, 1952)’s seminal article. According to these voting rules, an alternative is socially chosen if and only if it obtains the relative majority of votes and the total number of voters not abstaining reaches the quorum.     

Missing values: sparse inverse covariance estimation and?an?extension to sparse regression

We propose an ℓ ₁-regularized likelihood method for estimating the inverse covariance matrix in the high-dimensional multivariate normal model in presence of missing data. Our method is based on the assumption that the data are missing at random (MAR) which entails also the completely missing at random case. The implementation of the method is non-trivial as the observed negative log-likelihood generally is a complicated and non-convex function. We propose an efficient EM algorithm for optimization with provable numerical convergence properties. Furthermore, we extend the methodology to handle missing values in a sparse regression context. We demonstrate both methods on simulated and real data.     

Diagnostics of prior-data agreement in applied Bayesian analysis

This article focused on the definition and the study of a binary Bayesian criterion which measures a statistical agreement between a subjective prior and data information. The setting of this work is concrete Bayesian studies. It is an alternative and a complementary tool to the method recently proposed by Evans and Moshonov, [M. Evans and H. Moshonov, Checking for Prior-data conflict, Bayesian Anal. 1 (2006), pp. 893–914]. Both methods try to help the work of the Bayesian analyst, from preliminary to the posterior computation. Our criterion is defined as a ratio of Kullback–Leibler divergences; two of its main features are to make easy the check of a hierarchical prior and be used as a default calibration tool to obtain flat but proper priors in applications. Discrete and continuous distributions exemplify the approach and an industrial case study in reliability, involving the Weibull distribution, is highlighted.     

Resolving Coparenting Dissatisfaction In Couples: A Preliminary Task Analysis Study

This study explored the change that unfolded when parents resolved their coparenting dissatisfaction during an Integrative Brief Systemic Intervention (IBSI) for parent couples. We conducted a task analysis (Greenberg, 2007) to build a model of resolving coparenting dissatisfaction. We compared a postulated model of change (rational model) based on theoretical and clinical assumptions to the observations of the actual change process that couples experienced in an IBSI (empirical analysis). The empirical analysis was conducted on six IBSI therapy cases (three exhibiting positive development and three exhibiting no development). We defined positive development in IBSI as moving from coparenting dissatisfaction to coparenting satisfaction. The final rational–empirical model included six steps that facilitated the resolution of coparenting dissatisfaction. This study contributes to deepening the knowledge of how coparenting may change during marital therapy.     

Always doing your best? Effort and performance in dynamic settings

Theory and Decision - Achieving an ambitious goal frequently requires succeeding in a sequence of intermediate tasks, some being critical for the final outcome, and others not. However, individuals...     

A data mining framework for targeted category promotions

This research presents a new approach to derive recommendations for segment-specific, targeted marketing campaigns on the product category level. The proposed methodological framework serves as a decision support tool for customer relationship managers or direct marketers to select attractive product categories for their target marketing efforts, such as segment-specific rewards in loyalty programs, cross-merchandising activities, targeted direct mailings, customized supplements in catalogues, or customized promotions. The proposed methodology requires customers’ multi-category purchase histories as input data and proceeds in a stepwise manner. It combines various data compression techniques and integrates an optimization approach which suggests candidate product categories for segment-specific targeted marketing such that cross-category spillover effects for non-promoted categories are maximized. To demonstrate the empirical performance of our proposed procedure, we examine the transactions from a real-world loyalty program of a major grocery retailer. A simple scenario-based analysis using promotion responsiveness reported in previous empirical studies and prior experience by domain experts suggests that targeted promotions might boost profitability between 15 % and 128 % relative to an undifferentiated standard campaign.     

Emotional labour profiles: Associations with key predictors and outcomes

ABSTRACT

The present study examines how three emotional labour strategies (hiding feelings, faking emotions, and deep acting) combine within different profiles of workers among two samples characterised by different types and intensity of customer contact. In addition, this research investigates the role of perceived workload as well as perceived organisational support, supervisor support, and colleagues support in the prediction of profile membership. Finally, this research also documents the relation between emotional labour profiles and adaptive and maladaptive work outcomes (job satisfaction, work performance, emotional exhaustion, sleeping problems, psychological detachment, and counterproductive work behaviours). Latent profile analysis revealed three similar emotional labour profiles in both samples. Results also showed the most desirable levels on all outcomes to be associated with Profile 3 (Low Emotional Labor/Low Surface Acting and Moderate Deep Acting), followed by Profile 2 (Moderate Emotional Labor/Moderate Surface Acting and High Deep Acting) and Profile 1 (High Emotional Labor), with most comparisons being statistically significant in both samples. In contrast, a more diversified pattern of findings was observed in the prediction of profile membership. For instance, perceived colleagues support did not predict membership into any of the profiles, while supervisor support predicted an increased likelihood of membership into Profile 3 relative to Profiles 1 and 2.     

Nonparametric Estimation of the Probability of Detection of Flaws in an Industrial Component,from Destructive and Nondestructive Testing Data,Using Approximate Bayesian Computation

We consider the problem of estimating the probability of detection (POD) of flaws in an industrial steel component. Modeled as an increasing function of the flaw height, the POD characterizes the detection process; it is also involved in the estimation of the flaw size distribution, a key input parameter of physical models describing the behavior of the steel component when submitted to extreme thermodynamic loads. Such models are used to assess the resistance of highly reliable systems whose failures are seldom observed in practice. We develop a Bayesian method to estimate the flaw size distribution and the POD function, using flaw height measures from periodic in‐service inspections conducted with an ultrasonic detection device, together with measures from destructive lab experiments. Our approach, based on approximate Bayesian computation (ABC) techniques, is applied to a real data set and compared to maximum likelihood estimation (MLE) and a more classical approach based on Markov Chain Monte Carlo (MCMC) techniques. In particular, we show that the parametric model describing the POD as the cumulative distribution function (cdf) of a log‐normal distribution, though often used in this context, can be invalidated by the data at hand. We propose an alternative nonparametric model, which assumes no predefined shape, and extend the ABC framework to this setting. Experimental results demonstrate the ability of this method to provide a flexible estimation of the POD function and describe its uncertainty accurately.