The main objective of this study was to develop valid statistical collision models for multilane highway segments with or without curbs. For this, road geometric data, traffic data, and collision data for the three years were collected. The data include 2,274 collisions and 885 injury collisions...

Many Intelligent Transportation System (ITS) applications under the umbrella of Advanced Traffic Management Systems (ATMS) and Advanced Traveler Information Services (ATIS) call for the ability to anticipate future traffic conditions. Short-term traffic forecasting models play a central role in...

In this paper, we consider how to recover the structure of a Bayesian network from a moral graph. We present a more accurate characterization of moral edges, based on which a complete subset (i.e., a separator) contained in the neighbor set of one vertex of the putative moral edge in some prime...

Document classification is an area of great importance for which many classification methods have been developed. However, most of these methods cannot generate time-dependent classification rules. Thus, they are not the best choices for problems with time-varying structures. To address this...

In this note, we present three equivalent characterizations of a sufficient condition for χ2-asymptotics for the likelihood ratio tests in one-factor analysis offered by Drton (2009). A corollary of this result is that the condition is equivalent to the one-factor case of a condition provided...

The problem of regression shrinkage and selection for multivariate regression is considered. The goal is to consistently identify those variables relevant for regression. This is done not only for predictors but also for responses. To this end, a novel relationship between multivariate...

G. R. Ducharme and Y. Lepage (1986, J. Roy. Statist. Soc. Ser. B48, 197-205) presented the strong collapsibility of odds ratio in 22K tables. However, the concept is not suitable for an ordinal background variable since it is meaningless to pool nonadjacent levels in this case. In this paper, we...

This paper is concerned with situations in which estimating equations involve missing data and the full likelihood may not be available. We present an iterative algorithm for solving estimating equations in the presence of missing data. An application is made to a real data set from a...