M-ary detection filters for Cox process models

M-ary detection filters for Cox process models are derived. The models considered consist of Poisson observations and a discrete state Markov process whose value determines the intensity. The detection filters presented are stochastic partial differential equations driven by an observation process. The probabilities which solve these equations, indicate the relative likelihood that a given dynamical system explains an observation. A simulation study is included