Risk Analysis of Safety Service Patrol (SSP) Systems in Virginia

The transportation infrastructure is a vital backbone of any regional economy as it supports workforce mobility, tourism, and a host of socioeconomic activities. In this article, we specifically examine the incident management function of the transportation infrastructure. In many metropolitan regions, incident management is handled primarily by safety service patrols (SSPs), which monitor and resolve roadway incidents. In Virginia, SSP allocation across highway networks is based typically on average vehicle speeds and incident volumes. This article implements a probabilistic network model that partitions “business as usual” traffic flow with extreme‐event scenarios. Results of simulated network scenarios reveal that flexible SSP configurations can improve incident resolution times relative to predetermined SSP assignments.     

On the Testability of Identification in Some Nonparametric Models With Endogeneity

This paper examines three distinct hypothesis testing problems that arise in the context of identification of some nonparametric models with endogeneity. The first hypothesis testing problem we study concerns testing necessary conditions for identification in some nonparametric models with endogeneity involving mean independence restrictions. These conditions are typically referred to as completeness conditions. The second and third hypothesis testing problems we examine concern testing for identification directly in some nonparametric models with endogeneity involving quantile independence restrictions. For each of these hypothesis testing problems, we provide conditions under which any test will have power no greater than size against any alternative. In this sense, we conclude that no nontrivial tests for these hypothesis testing problems exist.     

Shorter hours wanted? A systematic review of working-time preferences and outcomes

Changes in working time have important economic, social and environmental implications. However, research on workers' preferences is highly fragmented across disciplines and journals. To overcome this, the present article provides a systematic review of the literature, analysing 173 studies. The study shows that working-time outcomes and mismatches are mostly studied in a small group of OECD countries, using survey data and statistical methods. The most clear and consistent results are about gender, care responsibilities and current working hours. Among professions, only the medical workforce receives substantial attention. Norms and preference formation are poorly understood, and more qualitative research is essential to understand how working-time reductions could spread.     

A Metropolis algorithm to obtain co-sufficient samples with applications in conditional tests

ABSTRACT

Conditional tests are constructed by conditioning a fit measure to a minimal sufficient statistic. To calculate the p-value of these tests, Monte Carlo methods with co-sufficient samples can be used. In this paper we show how to simulate co-sufficient samples when the data distribution belongs to the exponential family with doubly transitive sufficient statistics. The proposed method is illustrated using the beta distribution.     

A Note on Influence Assessment in Score Tests

Recently, [1] Ebrahimi, N. 1996. How to measure uncertainty about residual life time. Sankhya Ser. A, 58: 48–57.  [Google Scholar] proposed a dynamic measure based on differential entropy applied to the residual lifetime. This measure has been used for the classification and ordering of survival functions. More recently, [2] Ebrahimi, N. 1997. Testing whether lifetime distribution is decreasing uncertainty. Journal of Statistical Planning and Inference, 64: 9–19. [Crossref], [Web of Science ®] , [Google Scholar] has considered the problem of testing the monotonicity of this measure. We propose and study several kernel type estimators of the entropy of residual life through the estimation of f(x) log f(x). These estimators can be applied to the classification and comparison of lifetime distribution.     

Confidence Intervals for the Hyperparameters in Structural Models

This article deals with the bootstrap as an alternative method to construct confidence intervals for the hyperparameters of structural models. The bootstrap procedure considered is the classical nonparametric bootstrap in the residuals of the fitted model using a well-known approach. The performance of this procedure is empirically obtained through Monte Carlo simulations implemented in Ox. Asymptotic and percentile bootstrap confidence intervals for the hyperparameters are built and compared by means of the coverage percentages. The results are similar but the bootstrap procedure is better for small sample sizes. The methods are applied to a real time series and confidence intervals are built for the hyperparameters.     

Training Intraverbal Naming to Establish Matching-to-Sample Performances

The current study evaluated whether training intraverbal naming would be sufficient to establish visual-visual matching-to-sample (MTS) performances in college students. In the first experiment, we used a multiple-probe design across stimulus sets to assess whether six participants could match arbitrary visual stimuli (AB) after learning to tact their two experimentally defined classes (A’ and B’) and then intraverbally relate their names (i.e., “A’ goes with B’”). All participants matched the stimuli accurately after training, as well as emitted the trained intraverbals. In the second experiment, we used a multiple baseline design across four participants to assess whether the same training would produce bi-directional intraverbals in the form of “B’ goes with A’,” and MTS performance consistent with symmetry (BA). All participants responded accurately during matching and intraverbal tests. Across both experiments, participants stated the trained intraverbals while performing the matching task. Results showed that MTS performance can be established solely by verbal behavior training.