Practical Model Building for Quantitative Population Ethology with Event-Driven Competing Risks

by

Bland Ewing, Brian S. Yandell, James F. Barbieri, and Robert F. Luck
Technical Report #1034, 17 January 2001, U WI Madison Statistics

Ideas have been presented elsewhere on a framework for quantitative population ethology using event-driven competing risks. In today's climate, it is not enough to have an idea--one must have an implementation of the idea. To that end, we present the beginnings of such a system built on a public domain, statistical system called R. We use spline-based graphical tools to craft the mean value functions of the competing risk structure, based either on data or on prior belief. Spatial location of individuals is developed on a hexagonal grid at the resolution of the model, with a triangular coordinate system to reduce computation of distances. The components can be quickly developed and tested in R, and later translated to C for more efficient coding of the most highly used loops. We also discuss some of the design requirements that affect the development of an efficient competing risk model of large problems.

Click to get manuscript. The figures are not quite complete yet [Figure 1 was redone; Figure 4 is missing; Figure 9 is out of place], although this should be rectified presently.