An empirical Bayes approach to outliers

A formulation of the problem of detecting outliers as an empirical Bayes problem is studied. In so doing we encounter a non-standard empirical Bayes problem for which the notion of average risk asymptotic optimality (a.r.a.o.) of procedures is defined. Some general theorems giving sufficient conditions for a.r.a.o. procedures are developed. These general results are then used in various formulations of the outlier problem for underlying normal distributions to give a.r.a.o. empirical Bayes procedures. Rates of convergence results are also given using the methods of Johns and Van Ryzin (1971, 1972).     

Optimal correction for continuity in the chi-squared test in 2×2 tables

The most common asymptotic procedure for analyzing a 2 × 2 table (under the conditioning principle) is the ‰ chi-squared test with correction for continuity (c.f.c). According to the way this is applied, up to the present four methods have been obtained: one for one-tailed tests (Yates') and three for two-tailed tests (those of Mantel, Conover and Haber). In this paper two further methods are defined (one for each case), the 6 resulting methods are grouped in families, their individual behaviour studied and the optimal is selected. The conclusions are established on the assumption that the method studied is applied indiscriminately (without being subjected to validity conditions), and taking a basis of 400,000 tables (with the values of sample size n between 20 and 300 and exact P-values between 1% and 10%) and a criterion of evaluation based on the percentage of times in which the approximate P-value differs from the exact (Fisher's exact test) by an excessive amount. The optimal c.f.c. depends on n, on E (the minimum quantity expected) and on the error α to be used, but the rule of selection is not complicated and the new methods proposed are frequently selected. In the paper we also study what occurs when E ≥ 5, as well as whether the chi-squared by factor (n-1).     

Comparative analysis of modern optimization tools for the p-median problem

This paper develops a study on different modern optimization techniques to solve the p-median problem. We analyze the behavior of a class of evolutionary algorithm (EA) known as cellular EA (cEA), and compare it against a tailored neural network model and against a canonical genetic algorithm for optimization of the p-median problem. We also compare against existing approaches including variable neighborhood search and parallel scatter search, and show their relative performances on a large set of problem instances. Our conclusions state the advantages of using a cEA: wide applicability, low implementation effort and high accuracy. In addition, the neural network model shows up as being the more accurate tool at the price of a narrow applicability and larger customization effort.     

Connectivity and Resilience: A Multidimensional Analysis of Infrastructure Impacts in the Southwestern Amazon

Infrastructure is a worldwide policy priority for national development via regional integration into the global economy. However, economic, ecological and social research draws contrasting conclusions about the consequences of infrastructure. We present a synthetic approach to the study of infrastructure, focusing on a multidimensional treatment of indicators of connectivity and resilience. As our study case, we adopt a tri-national frontier in the southwestern Amazon being integrated by a highway, and use survey data for rural leaders to evaluate the relationship of community connectivity to market towns and social-ecological resilience. The findings show varying relationships among different dimensions of connectivity and resilience, which bear implications regarding indicator approaches to the study of infrastructure impacts.     

Social Optimal Location of Facilities with Fixed Servers,Stochastic Demand,and Congestion

We consider two capacity choice scenarios for the optimal location of facilities with fixed servers, stochastic demand, and congestion. Motivating applications include virtual call centers, consisting of geographically dispersed centers, walk‐in health clinics, motor vehicle inspection stations, automobile emissions testing stations, and internal service systems. The choice of locations for such facilities influences both the travel cost and waiting times of users. In contrast to most previous research, we explicitly embed both customer travel/connection and delay costs in the objective function and solve the location–allocation problem and choose facility capacities simultaneously. The choice of capacity for a facility that is viewed as a queueing system with Poisson arrivals and exponential service times could mean choosing a service rate for the servers (Scenario 1) or choosing the number of servers (Scenario 2). We express the optimal service rate in closed form in Scenario 1 and the (asymptotically) optimal number of servers in closed form in Scenario 2. This allows us to eliminate both the number of servers and the service rates from the optimization problems, leading to tractable mixed‐integer nonlinear programs. Our computational results show that both problems can be solved efficiently using a Lagrangian relaxation optimization procedure.     

ON THE IMPUTATION OF RENTAL PRICES TO OWNER‐OCCUPIED HOUSING

This paper challenges the usual objections to the possibility of applying the rental equivalent approach to determine the weight that nonrental housing services should have in the Consumer Price Index (CPI). Using data from two Spanish household budget surveys, it is shown that market rents can be well represented in terms of an index of housing quality, two geographical variables, and the year of occupancy. This parsimonious empirical model is used to impute a rental value to nonrental housing units, taking into account the possible selection bias induced by systematic differences in housing characteristics between the market rental sector and the nonrental stock. On average, the estimated hedonic values are relatively close to the self‐imputations provided in the household surveys by the occupants of such dwellings. Therefore, using either of the two alternatives to assess the importance of nonrental housing services in the CPI have small consequences for inflation. Instead, dropping these services from the CPI creates a downward bias in the measurement of inflation of 0.33 percentage points per year during 1985–1992, and an upward bias of 0.38 percentage points per year during 1993 to 2000. (JEL: C43, D12, R21, C21, E31)     

Two Applications of Statistics to Traffic Models

Two statistical applications for estimation and prediction of flows in traffic networks are presented. In the first, the number of route users are assumed to be independent α-shifted gamma Γ(θ, λ₀) random variables denoted H(α, θ, λ₀), with common λ₀. As a consequence, the link, OD (origin-destination) and node flows are also H(α, θ, λ₀) variables. We assume that the main source of information is plate scanning, which permits us to identify, totally or partially, the vehicle route, OD and link flows by scanning their corresponding plate numbers at an adequately selected subset of links. A Bayesian approach using conjugate families is proposed that allows us to estimate different traffic flows. In the second application, a stochastic demand dynamic traffic model to predict some traffic variables and their time evolution in real networks is presented. The Bayesian network model considers that the variables are generalized Beta variables such that when marginally transformed to standard normal become multivariate normal. The model is able to provide a point estimate, a confidence interval or the density of the variable being predicted. Finally, the models are illustrated by their application to the Nguyen Dupuis network and the Vermont-State example. The resulting traffic predictions seem to be promising for real traffic networks and can be done in real time.     

Motivational factors and physician advice for physical activity in older urban adults

This study aimed to ascertain by means of a new scale older adults' motives for engaging in physical activity, in a probability and representative sample of an older urban population. The sample size was 630 older adults, ranging from 65 to 94 years in age, randomly selected using multistage sampling. The participants completed a 17-item questionnaire, as well as answering questions on demographic variables, type of demand for physical activity, and physician's recommendation. A principal-component analysis was performed. The relationships among the four factors (physical health, social relationships, competence, and physician's advice) show a clearly motivational structure. Significant relationships have also been found between physician's recommendation and type of demand. The findings suggest that programs promoting physical activity in older adults should have different characteristics from those aimed at general adult populations.     

Mitigating the political participation gap from the school: the roles of civic knowledge and classroom climate

Empirical evidence has consistently shown that political participation is positively related with socioeconomic background. Furthermore, recent research suggests that children who come from low status families are already less willing to get politically involved. The present paper aims to analyze the possible impact that schools can have in mitigating the effect of parents' socioeconomic status on students' expected electoral participation, focusing on two variables: civic knowledge and classroom climate. The analyses are based on a series of multilevel models using Chilean data of the International Civic and Citizenship Education Study 2009. The results support the influence of students' socioeconomic background on expected electoral participation. Furthermore, civic knowledge and classroom climate show a positive and similar influence on students' expected participation. However, classroom climate appears less affected by students' background than civic knowledge, opening the discussion about which strategy should be emphasized when aiming to mitigate the political participation gap.