Discrete Dynamics in Nature and Society
Volume 7 (2002), Issue 3, Pages 177-189
doi:10.1080/1026022021000001454
Identification problem for stochastic models with application to carcinogenesis, cancer detection and radiation biology
Department of Mathematics, Idaho State University and Huntsman Cancer Institute of the University of Utah, Idaho State University, Pocatello 83209-8085, ID, USA
Received 16 June 2001
Copyright © 2002 L. G. Hanin. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
A general framework for solving identification problem for a broad class of deterministic and stochastic models is discussed. This methodology allows for a unified approach to studying identifiability of various stochastic models arising in biology and medicine including models of spontaneous and induced Carcinogenesis, tumor progression and detection, and randomized hit and target models of irradiated cell survival. A variety of known results on parameter identification for stochastic models is reviewed and several new results are presented with an emphasis on rigorous mathematical development.