Man pages for pomp
Statistical Inference for Partially Observed Markov Processes

abcEstimation by approximate Bayesian computation (ABC)
basic-probesSome useful probes for partially-observed Markov processes
blowfliesModel for Nicholson's blowflies.
bsmcThe Liu and West Bayesian particle filter
bsplinesB-spline bases
builderWrite, compile, and build a pomp object using native codes
csnippetC code snippets for accelerating computations
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.
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
particles-mifGenerate particles from the user-specified distribution.
pfilterParticle filter
pluginsPlug-ins for state-process models
pmcmcThe particle Markov chain Metropolis-Hastings algorithm
pompConstructor of the basic POMP object
pomp-funDefinition and methods of the "pomp.fun" 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...
pomp documentation built on May 2, 2019, 4:09 p.m.