Man pages for kingaa/pomp
Statistical Inference for Partially Observed Markov Processes

abcEstimation by approximate Bayesian computation (ABC)
bakeTools for reproducible computations.
basic_probesSome useful probes for partially-observed Markov processes
blowfliesModel for Nicholson's blowflies.
bsmcThe Liu and West Bayesian particle filter
bsplinesB-spline bases
daccaModel of cholera transmission for historic Bengal.
designDesign matrices for pomp calculations
eulermultinomThe Euler-multinomial distributions and Gamma white-noise...
exampleExamples of the construction of POMP models
gompertzGompertz model with log-normal observations.
kalmanEnsemble Kalman filters
logmeanexpThe log-mean-exp trick
lowlevelpomp low-level interface
measlesHistorical childhood disease incidence data
mifMaximum likelihood by iterated filtering
mif2IF2: Maximum likelihood by iterated, perturbed Bayes maps
nlfParameter estimation my maximum simulated quasi-likelihood...
ou2Two-dimensional discrete-time Ornstein-Uhlenbeck process
packageInference for partially observed Markov processes
parmatCreate a matrix of parameters
pfilterParticle filter
pmcmcThe particle Markov chain Metropolis-Hastings algorithm
pompConstructor of the basic pomp object
pomp_funDefinition and methods of the "" class
pomp_methodsFunctions for manipulating, displaying, and extracting...
probeProbe a partially-observed Markov process by computing...
proposalsMCMC proposal distributions
rickerRicker model with Poisson observations.
rw2Two-dimensional random-walk process
sannboxSimulated annealing with box constraints.
simulate_pompSimulations of a partially-observed Markov process
sirCompartmental epidemiological models
spectPower spectrum computation and spectrum-matching for...
traj_matchParameter estimation by fitting the trajectory of a model's...
kingaa/pomp documentation built on June 23, 2018, 6:03 p.m.