Define a model to use throughout the examples in this file
Use the first 400 simulations to determine the full-joint posterior of the poisson model
Run the filter over the last 100 elements of the simulted data using samples from the joint-posterior of the state and parameters, p(x, theta | y)
Perform a long term forecast, by sampling from the full joint posterior p(x, theta | y) a pair consisting of the state at the time of the last observation and the associated parameter*value
Perform a one step forecast of the data
Perform a one step forecast on the poisson data, using unseen test data, Sampling from the joint posterior of the parameters and the state p(x, theta | y)
Perform a pilot run of the PMMH algorithm, to determine the optimum number of particles to use in the particle filter
Determine how many particles are required to run the MCMC
Simulate an SDE
Simulate a poisson model, with seasonal rate parameter