Stochastic modeling of carcinogenesis: State space models and estimation of parameters
W. Y. Tan, L.-J. Zhang, C.W. Chen · Discrete and Continuous Dynamical Systems - B · 2004
In this paper we have developed a state space model for carcinogenesis. By using this state space model we have also developed statistical procedures to estimate the unknown parameters via multi-level Gibbs sampling method. We have applied this model and the methods to the British physician data on lung cancer with smoking. Our results indicate that the tobacco nicotine is an initiator. If $t > 60$ years old, then the tobacco nicotine is also a promoter.