Generic Identification of Binary-Valued Hidden Markov Processes Algebraic Statistics Hidden Markov Processes Generic Identification The generic identification problem is to decide whether a stochastic process (X_t) is a hidden Markov process and if yes to infer its parameters for all but a subset of parametrizations that form a lower-dimensional subvariety in parameter space. Partial answers so far available depend on extra assumptions on the processes, which are usually centered around stationarity. Here we present a general solution for binary-valued hidden Markov processes. Our approach is rooted in algebraic statistics hence it is geometric in nature. We find that the algebraic varieties associated with the probability distributions of binary-valued hidden Markov processes are zero sets of determinantal equations which draws a connection to well-studied objects from algebra. As a consequence, our solution allows for algorithmic implementation based on elementary (linear) algebraic routines. Schönhuth, Alexander 2014 2014-04-30 Article application/pdf islandora:1007820 http://hdl.handle.net/10560/islandora:1007820 MATH / Applied Mathematics Illinois Institute of Technology Journal of Algebraic Statistics en Open Access