Bayesian sequential Monte Carlo
                        The Liu and West Bayesian particle filter
Example pomp models     Examples of the construction of POMP models
LondonYorke             Historical childhood disease incidence data
MCMC proposal distributions
                        MCMC proposal distributions
Nonlinear forecasting   Parameter estimation my maximum simulated
                        quasi-likelihood (nonlinear forecasting)
POMP simulation         Simulations of a partially-observed Markov
                        process
Power spectrum computation and matching
                        Power spectrum computation and
                        spectrum-matching for partially-observed Markov
                        processes
Probe functions         Some useful probes for partially-observed
                        Markov processes
Probes and synthetic likelihood
                        Probe a partially-observed Markov process by
                        computing summary statistics and the synthetic
                        likelihood.
Simulated annealing     Simulated annealing with box constraints.
Trajectory matching     Parameter estimation by fitting the trajectory
                        of a model's deterministic skeleton to data
abc                     Estimation by approximate Bayesian computation
                        (ABC)
bake                    Tools for reproducible computations.
blowflies               Model for Nicholson's blowflies.
bspline.basis           B-spline bases
dacca                   Model of cholera transmission for historic
                        Bengal.
ensembe Kalman filter   Ensemble Kalman filters
euler.sir               Compartmental epidemiological models
eulermultinom           The Euler-multinomial distributions and Gamma
                        white-noise processes
gompertz                Gompertz model with log-normal observations.
hitch                   Hitching C snippets and R functions to pomp.fun
                        objects
logmeanexp              The log-mean-exp trick
mif                     Maximum likelihood by iterated filtering
mif2                    IF2: Maximum likelihood by iterated, perturbed
                        Bayes maps
ou2                     Two-dimensional discrete-time
                        Ornstein-Uhlenbeck process
parmat                  Create a matrix of parameters
particle filter         Particle filter
pmcmc                   The particle Markov chain Metropolis-Hastings
                        algorithm
pomp constructor        Constructor of the basic pomp object
pomp low-level interface
                        pomp low-level interface
pomp methods            Functions for manipulating, displaying, and
                        extracting information from objects of the
                        'pomp' class
pomp-package            Inference for partially observed Markov
                        processes
profileDesign           Design matrices for pomp calculations
ricker                  Ricker model with Poisson observations.
rw2                     Two-dimensional random-walk process
