Computation of determinantal subset influence in regression

One of the important goals of regression diagnostics is the detection of cases or groups of cases which have an inordinate impact on the regression results. Such observations are generally described as influential. A number of influence measures have been proposed, each focusing on a different aspect of the regression. For single cases, these measures are relatively simple and inexpensive to calculate. However, the detection of multiple-case or joint influence is more difficult on two counts. First, calculation of influence for a single subset is more involved than for an individual case, and second, the sheer number of subsets of cases makes the computation overwhelming for all but the smallest data sets.Barrett and Gray (1992) described methods for efficiently examining subset influence for those measures that can be expressed as the trace of a product of positive semidefinite (psd) matrices. There are, however, other popular measures that do not take this form, but rather are expressible as the ratio of determinants of psd matrices. This article focuses on reducing the computation for the determinantal ratio measures by making use of upper and lower bounds on the influence to limit the number of subsets for which the actual influence must be explicitly determined.     

Immigration,Repatriation, and Deportation: The Mexican‐Origin Population in the United States, 1920–1950

Scholars conventionally assert that government authorities forcibly expelled 500,000 persons of Mexican origin from the U.S. in the 1930s, with more than half of those removed U.S. citizens. Estimates using census data indicate substantially lower numbers, limited governmental involvement, fewer citizens, and considerable voluntary departure. Voluntary decisions fit the repatriation strategy that had been common among young Mexican immigrants in the 1920s. Ironically, the 1940s Bracero Program, designed by Mexico and the U.S. to replicate the 1920s pattern of circular migration, led instead to massive illegal immigration and unprecedented levels of deportation.     

A communicative planning approach to combat graduate unemployment in Saudi Arabia

Abstract

This paper introduces and critically reviews the Saudi education and unemployment situation. It sets out the specialized nature of issues regarding education and unemployment which are seldom found in other countries. The governmental efforts and subsequent results in the employment sectors are investigated to illustrate the reasons behind prevailing and expected future graduate unemployment. In addition, this paper proposes the application of a combination of a rational planning model and the concept of communicative rationality in solving the problem of graduate unemployment in Saudi Arabia. It asserts the need for comprehensive data on the nature and magnitude of unemployment, and adequate consultation with all the stakeholders including the private sector. A brief survey conducted among the graduates of King Fahd University of Petroleum &; Minerals (KFUPM) reveals that, while they are competent and easily absorbed into the market, the scenario is not the same for other educational institutions. Similar studies for other educational institutions will facilitate an understanding of the extent of coordination with the job market. A study is being conducted to enhance the creation of a link between the market demand for educational programs and programs offered by educational institutes.     

Still standing after all these years: the presence and internet presentation of religious buildings in the Chicago area, 1936–2016

Scholars have examined the changes in religious architecture over time but few have focused on the ongoing presence of religious buildings in communities nor how long-standing congregations interact with their older building. This study utilises two Internet data sources – Google Street View and the websites of religious congregations – to examine the fate and online presentation of the buildings of four Protestant denominations in the Chicago region from 1936 to today: Disciples of Christ, Lutheran Church-Missouri Synod, Presbyterian, and Seventh-day Adventist. The patterns found show the stability of many church buildings over eight decades and how they help anchor some religious groups – even though newer congregations use a number of these structures – yet congregations make unique choices about presenting their buildings through their website. These findings suggest religious buildings continue to influence their original religious congregations, newer groups using the building and neighbourhoods decades after they are constructed.     

A Flexible Hierarchical Bayesian Modeling Technique for Risk Analysis of Major Accidents

Safety analysis of rare events with potentially catastrophic consequences is challenged by data scarcity and uncertainty. Traditional causation‐based approaches, such as fault tree and event tree (used to model rare event), suffer from a number of weaknesses. These include the static structure of the event causation, lack of event occurrence data, and need for reliable prior information. In this study, a new hierarchical Bayesian modeling based technique is proposed to overcome these drawbacks. The proposed technique can be used as a flexible technique for risk analysis of major accidents. It enables both forward and backward analysis in quantitative reasoning and the treatment of interdependence among the model parameters. Source‐to‐source variability in data sources is also taken into account through a robust probabilistic safety analysis. The applicability of the proposed technique has been demonstrated through a case study in marine and offshore industry.     

NONLINEAR TUBE-FITTING FOR THE ANALYSIS OF ANATOMICAL AND FUNCTIONAL STRUCTURES

We are concerned with the estimation of the exterior surface and interior summaries of tube-shaped anatomical structures. This interest is motivated by two distinct scientific goals, one dealing with the distribution of HIV microbicide in the colon and the other with measuring degradation in white-matter tracts in the brain. Our problem is posed as the estimation of the support of a distribution in three dimensions from a sample from that distribution, possibly measured with error. We propose a novel tube-fitting algorithm to construct such estimators. Further, we conduct a simulation study to aid in the choice of a key parameter of the algorithm, and we test our algorithm with validation study tailored to the motivating data sets. Finally, we apply the tube-fitting algorithm to a colon image produced by single photon emission computed tomography (SPECT) and to a white-matter tract image produced using diffusion tensor imaging (DTI).     

An Integrated Scenario Ensemble-Based Framework for Hurricane Evacuation Modeling: Part 1—Decision Support System

This article introduces a new integrated scenario-based evacuation (ISE) framework to support hurricane evacuation decision making. It explicitly captures the dynamics, uncertainty, and human–natural system interactions that are fundamental to the challenge of hurricane evacuation, but have not been fully captured in previous formal evacuation models. The hazard is represented with an ensemble of probabilistic scenarios, population behavior with a dynamic decision model, and traffic with a dynamic user equilibrium model. The components are integrated in a multistage stochastic programming model that minimizes risk and travel times to provide a tree of evacuation order recommendations and an evaluation of the risk and travel time performance for that solution. The ISE framework recommendations offer an advance in the state of the art because they: (1) are based on an integrated hazard assessment (designed to ultimately include inland flooding), (2) explicitly balance the sometimes competing objectives of minimizing risk and minimizing travel time, (3) offer a well-hedged solution that is robust under the range of ways the hurricane might evolve, and (4) leverage the substantial value of increasing information (or decreasing degree of uncertainty) over the course of a hurricane event. A case study for Hurricane Isabel (2003) in eastern North Carolina is presented to demonstrate how the framework is applied, the type of results it can provide, and how it compares to available methods of a single scenario deterministic analysis and a two-stage stochastic program.