Functions for constucting generic Metropolis-Hastings MCMC algorithms, and associated utilities.
Functions associated with particle filtering of Markov process models against time series data and the computation of marginal model likelihoods.
Functions for simulating data associated with a Markov process given an appropriate transition kernel.
Some example SPN models, each of which can be instantiated with either discrete or continous states.
Functions which accept a Spn
and return a function for simulating from the transition kernel of that model
Object containing basic types used throughout the library.
Functions for constucting generic Metropolis-Hastings MCMC algorithms, and associated utilities. Can be used in conjunction with an unbiased estimate of marginal model likelihood for constructing pseudo-marginal MCMC algorithms, such as PMMH pMCMC.