Hidden Markov models with discrete non-parametric observation distributions Fits hidden Markov models with discrete non-parametric observation distributions to data sets. Simulates data from such models. Finds most probable underlying hidden states, the most probable sequences of such states, and the log likelihood of a collection of observations given the parameters of the model. Software Depends: R (>= 0.99) Rolf Turner <r.turner@auckland.ac.nz> Rolf Turner <r.turner@auckland.ac.nz> and Limin Liu. GPL (>= 2) 2012-03-02 application/tgz http://CRAN.R-project.org/package=hmm.discnp