Discrete-event simulation modeling has become the most commonly used tool for performance evaluation of stochastic dynamic systems in science and engineering. The field operations of surveys can be classified as one of these stochastic dynamic systems. This paper describes the simulation and modeling of simplified field operations for NHIS (National Health Interview Survey). In particular, we a...

The paper demonstrates that a wide variety of event-based modeling approaches are based on special cases of the same general event concept, and that the general event concept can be used to unify the otherwise unrelated fields of information modeling and process modeling. A set of event-based modeling approaches are analyzed and the results are used to formulate a general event concept that can...

We present a probabilistic model of events in continuous time in which each event triggers a Poisson process of successor events. The ensemble of observed events is thereby modeled as a superposition of Poisson processes. Efficient inference is feasible under this model with an EM algorithm. Moreover, the EM algorithm can be implemented as a distributed algorithm, permitting the model to be app...

The history of climate modeling begins with conceptual models, followed in the 19th century by mathematical models of energy balance and radiative transfer, as well as simple analog models. Since the 1950s, the principal tools of climate science have been computer simulation models of the global general circulation. From the 1990s to the present, a trend toward increasingly comprehensive couple...

A lot of recent research has focused on methods of modeling Web users and on efficient ways to initialize and manage user models. In this paper, we present a new user modeling technique relying on a temporal, graph-based data model for semistructured information. Our technique can be used to filter WWW information and to make the Web experience personalized for the individual user. Moreover, su...

This paper presents practical guidance on conducting survival analysis using data derived from a complex sample survey. Survival curves, Cox models, and discrete-time logistic regression are demonstrated through use of PROC LIFETEST, PROC SGPLOT, PROC SURVEYPHREG and PROC SURVEYLOGISTIC. The analytic techniques presented can be used on any operating system and are intended for an intermediate l...