Logo image
State-space based mass event-history model I: many decision-making agents with one target
Journal article   Peer reviewed

State-space based mass event-history model I: many decision-making agents with one target

H. Fushing, L. Zhu, D.I. Shapiro-Ilan, J.F. Campbell and E.E. Lewis
Annals of Applied Statistics, Vol.2(4), pp.1503-1522
12/01/2008
PMCID: 2676853
PMID: 19421335

Abstract

A dynamic decision-making system that includes a mass of indistinguishable agents could manifest impressive heterogeneity. This kind of non-homogeneity is postulated to result from macroscopic behavioral tactics employed by almost all involved agents. A State-Space Based (SSB) mass event-history model is developed here to explore the potential existence of such macroscopic behaviors. By imposing an unobserved internal state-space variable into the system, each individual’s event-history is made into a composition of a common state duration and an individual specific time to action. With the common state modeling of the macroscopic behavior, parametric statistical inferences are derived under the current-status data structure and conditional independence assumptions. Identifiability and computation related problems are also addressed. From the dynamic perspectives of system-wise heterogeneity, this SSB mass event-history model is shown to be very distinct from a random effect model via the Principle Component Analysis (PCA) in a numerical experiment. Real data showing the mass invasion by two species of parasitic nematode into two species of host larvae are also analyzed. The analysis results not only are found coherent in the context of the biology of the nematode as a parasite, but also include new quantitative interpretations.
url
State-space based mass event-history model I: many decision-making agents with one targetView

Metrics

1 Record Views

Details

Logo image