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

abcApproximate Bayesian computation
accumulatorsaccumulators
as_data_frameCoerce to data frame
as_pompas.pomp
bakeBake, stew, and freeze
basic_probesUseful probes for partially-observed Markov processes
blowfliesNicholson's blowflies.
bsflubsflu
bsmc2The Liu and West Bayesian particle filter
bsplinesB-spline bases
coefExtract, set, or alter coefficients
concatConcatenate
cond_logLikConditional log likelihood
continueContinue an iterative calculation
covariate_tableCovariates
covmatEstimate a covariance matrix from algorithm traces
csnippetC snippets
daccaModel of cholera transmission for historic Bengal.
deprecatedDeprecated functions
designDesign matrices for pomp calculations
distributionsProbability distributions
dmeasuredmeasure
dmeasure_specThe measurement model density
dpriordprior
dprocessdprocess
dprocess_specThe latent state process density
eff_sample_sizeEffective sample size
filter_meanFiltering mean
filter_trajFiltering trajectories
forecastForecast mean
gompertzGompertz model with log-normal observations.
hitchHitching C snippets and R functions to pomp_fun objects
kalmanEnsemble Kalman filters
listieslisties
loadLoading and unloading shared-object libraries
loglikLog likelihood
logmeanexpThe log-mean-exp trick
lookupLookup table
measlesHistorical childhood disease incidence data
mif2Iterated filtering: maximum likelihood by iterated, perturbed...
nlfNonlinear forecasting
objfunObjective functions
obsobs
ou2Two-dimensional discrete-time Ornstein-Uhlenbeck process
parameter_transParameter transformations
parmatCreate a matrix of parameters
partranspartrans
parusparus
pfilterParticle filter
plotPlotting
pmcmcThe particle Markov chain Metropolis-Hastings algorithm
pompConstructor of the basic pomp object
pomp_classThe basic pomp class
pomp_funThe "pomp_fun" class
pomp-packageInference for partially observed Markov processes
pred_meanPrediction mean
pred_varPrediction variance
printPrint methods
prior_specprior specification
probeProbes (AKA summary statistics)
probe_matchProbe matching
proposalsMCMC proposal distributions
pStoppStop
reexportsObjects exported from other packages
resampleResample
rickerRicker model with Poisson observations.
rinitrinit
rinit_specThe initial-state distribution
rmeasurermeasure
rmeasure_specThe measurement-model simulator
rpriorrprior
rprocessrprocess
rprocess_specThe latent state process simulator
rw2Two-dimensional random-walk process
rw_sdrw.sd
sannboxSimulated annealing with box constraints.
showShow methods
simulateSimulations of a partially-observed Markov process
sirCompartmental epidemiological models
skeletonskeleton
skeleton_specThe deterministic skeleton of a model
spectPower spectrum
spect_matchSpectrum matching
spySpy
statesLatent states
summarySummary methods
timeMethods to manipulate the obseration times
timezeroThe zero time
tracesTraces
trajectoryTrajectory of a deterministic model
traj_matchTrajectory matching
transformationsTransformations
undefinedUndefined
userdataFacilities for making additional information to basic...
verhulstVerhulst-Pearl model
windowWindow
workhorsesWorkhorse functions for the 'pomp' algorithms.
kingaa/pomp documentation built on Sept. 24, 2018, 2:17 a.m.