# Statistical Inference for Partially Observed Markov Processes

## Documentation for package ‘pomp’ version 2.3

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

A B C D E F G H I K L M N O P R S T U V W

pomp-package | Inference for partially observed Markov processes

## -- A --

abc | Approximate Bayesian computation
abc-data.frame | Approximate Bayesian computation
abc-method | Approximate Bayesian computation
abc-pomp | Approximate Bayesian computation
accumulators | accumulators
accumvars | accumulators
as-csnippet | C snippets
as-method | Coerce to data frame
as-method | C snippets
as.data.frame | Coerce to data frame
as.data.frame.abcList | Coerce to data frame
as.data.frame.bsmcd_pomp | Coerce to data frame
as.data.frame.kalmand_pomp | Coerce to data frame
as.data.frame.mif2List | Coerce to data frame
as.data.frame.pfilterd_pomp | Coerce to data frame
as.data.frame.pfilterList | Coerce to data frame
as.data.frame.pmcmcList | Coerce to data frame
as.data.frame.pomp | Coerce to data frame
as.data.frame.pompList | Coerce to data frame
as.data.frame.probed_pomp | Coerce to data frame

## -- B --

bake | Bake, stew, and freeze
basic_probes | Useful probes for partially-observed Markov processes
blowflies | Nicholson's blowflies.
blowflies1 | Nicholson's blowflies.
blowflies2 | Nicholson's blowflies.
bsflu | Influenza outbreak in a boarding school
bsmc2 | The Liu and West Bayesian particle filter
bsmc2-data.frame | The Liu and West Bayesian particle filter
bsmc2-method | The Liu and West Bayesian particle filter
bsmc2-pomp | The Liu and West Bayesian particle filter
bspline.basis | B-spline bases
bsplines | B-spline bases

## -- C --

coef | Extract, set, or alter coefficients
coef-listie | Extract, set, or alter coefficients
coef-method | Extract, set, or alter coefficients
coef-objfun | Extract, set, or alter coefficients
coef-pomp | Extract, set, or alter coefficients
coef<- | Extract, set, or alter coefficients
coef<--method | Extract, set, or alter coefficients
coef<--pomp | Extract, set, or alter coefficients
coerce-method | Coerce to data frame
coerce-method | C snippets
coerce-method | Probes (AKA summary statistics)
coerce-method | Power spectrum
coerce-objfun-data.frame | Coerce to data frame
coerce-pomp-data.frame | Coerce to data frame
coerce-probe_match_objfun-probed_pomp | Probes (AKA summary statistics)
coerce-spect_match_objfun-spectd_pomp | Power spectrum
cond.logLik | Conditional log likelihood
cond.logLik-bsmcd_pomp | Conditional log likelihood
cond.logLik-kalmand_pomp | Conditional log likelihood
cond.logLik-method | Conditional log likelihood
cond.logLik-pfilterd_pomp | Conditional log likelihood
continue | Continue an iterative calculation
continue-abcd_pomp | Continue an iterative calculation
continue-method | Continue an iterative calculation
continue-mif2d_pomp | Continue an iterative calculation
continue-pmcmcd_pomp | Continue an iterative calculation
covariate_table | Covariates
covariate_table-character-method | Covariates
covariate_table-method | Covariates
covariate_table-numeric-method | Covariates
covmat | Estimate a covariance matrix from algorithm traces
covmat-abcd_pomp | Estimate a covariance matrix from algorithm traces
covmat-abcList | Estimate a covariance matrix from algorithm traces
covmat-method | Estimate a covariance matrix from algorithm traces
covmat-pmcmcd_pomp | Estimate a covariance matrix from algorithm traces
covmat-pmcmcList | Estimate a covariance matrix from algorithm traces
covmat-probed_pomp | Estimate a covariance matrix from algorithm traces
Csnippet | C snippets
Csnippet-class | C snippets

## -- D --

dacca | Model of cholera transmission for historic Bengal.
design | Design matrices for pomp calculations
deulermultinom | Probability distributions
discrete_time | The latent state process simulator
distributions | Probability distributions
dmeasure | dmeasure
dmeasure-method | dmeasure
dmeasure-pomp | dmeasure
dmeasure_spec | The measurement model density
dprior | dprior
dprior-method | dprior
dprior-pomp | dprior
dprocess | dprocess
dprocess-method | dprocess
dprocess-pomp | dprocess
dprocess_spec | The latent state process density

## -- E --

eakf | Ensemble Kalman filters
eakf-data.frame | Ensemble Kalman filters
eakf-method | Ensemble Kalman filters
eakf-pomp | Ensemble Kalman filters
ebola | Ebola outbreak, West Africa, 2014-2016
ebolaModel | Ebola outbreak, West Africa, 2014-2016
ebolaWA2014 | Ebola outbreak, West Africa, 2014-2016
eff.sample.size | Effective sample size
eff.sample.size-bsmcd_pomp | Effective sample size
eff.sample.size-method | Effective sample size
eff.sample.size-pfilterd_pomp | Effective sample size
enkf | Ensemble Kalman filters
enkf-data.frame | Ensemble Kalman filters
enkf-method | Ensemble Kalman filters
enkf-pomp | Ensemble Kalman filters
euler | The latent state process simulator
ewcitmeas | Historical childhood disease incidence data
ewmeas | Historical childhood disease incidence data
expit | Transformations

## -- F --

filter.mean | Filtering mean
filter.mean-kalmand_pomp | Filtering mean
filter.mean-method | Filtering mean
filter.mean-pfilterd_pomp | Filtering mean
filter.traj | Filtering trajectories
filter.traj-method | Filtering trajectories
filter.traj-pfilterd_pomp | Filtering trajectories
filter.traj-pfilterList | Filtering trajectories
filter.traj-pmcmcd_pomp | Filtering trajectories
filter.traj-pmcmcList | Filtering trajectories
flow | Flow of a deterministic model
flow-method | Flow of a deterministic model
flow-pomp | Flow of a deterministic model
Forecast | Forecast mean
forecast | Forecast mean
forecast-kalmand_pomp | Forecast mean
forecast-method | Forecast mean
freeze | Bake, stew, and freeze

## -- G --

gillespie | The latent state process simulator
gillespie_hl | The latent state process simulator
gompertz | Gompertz model with log-normal observations.

## -- H --

hitch | Hitching C snippets and R functions to pomp_fun objects

## -- I --

inv_log_barycentric | Transformations

## -- K --

kalman | Ensemble Kalman filters

## -- L --

logit | Transformations
logLik | Log likelihood
logLik-bsmcd_pomp | Log likelihood
logLik-kalmand_pomp | Log likelihood
logLik-method | Log likelihood
logLik-nlf_objfun | Log likelihood
logLik-objfun | Log likelihood
logLik-pfilterd_pomp | Log likelihood
logLik-pmcmcd_pomp | Log likelihood
logLik-probed_pomp | Log likelihood
logLik-spect_match_objfun | Log likelihood
logmeanexp | The log-mean-exp trick
log_barycentric | Transformations
LondonYorke | Historical childhood disease incidence data

## -- M --

map | The deterministic skeleton of a model
measles | Historical childhood disease incidence data
melt-method | Coerce to data frame
mif2 | Iterated filtering: maximum likelihood by iterated, perturbed Bayes maps
mif2-data.frame | Iterated filtering: maximum likelihood by iterated, perturbed Bayes maps
mif2-method | Iterated filtering: maximum likelihood by iterated, perturbed Bayes maps
mif2-mif2d_pomp | Iterated filtering: maximum likelihood by iterated, perturbed Bayes maps
mif2-pfilterd_pomp | Iterated filtering: maximum likelihood by iterated, perturbed Bayes maps
mif2-pomp | Iterated filtering: maximum likelihood by iterated, perturbed Bayes maps
mvn.diag.rw | MCMC proposal distributions
mvn.rw | MCMC proposal distributions
mvn.rw.adaptive | MCMC proposal distributions

## -- N --

nlf | Nonlinear forecasting
nlf_objfun | Nonlinear forecasting
nlf_objfun-data.frame | Nonlinear forecasting
nlf_objfun-method | Nonlinear forecasting
nlf_objfun-nlf_objfun | Nonlinear forecasting
nlf_objfun-pomp | Nonlinear forecasting

## -- O --

obs | obs
obs-method | obs
obs-pomp | obs
onestep | The latent state process simulator
ou2 | Two-dimensional discrete-time Ornstein-Uhlenbeck process

## -- P --

parameter_trans | Parameter transformations
parameter_trans-character,character | Parameter transformations
parameter_trans-Csnippet,Csnippet | Parameter transformations
parameter_trans-function,function | Parameter transformations
parameter_trans-method | Parameter transformations
parameter_trans-missing,missing | Parameter transformations
parmat | Create a matrix of parameters
partrans | partrans
partrans-method | partrans
partrans-pomp | partrans
parus | Parus major population dynamics
periodic.bspline.basis | B-spline bases
pfilter | Particle filter
pfilter-data.frame | Particle filter
pfilter-method | Particle filter
pfilter-objfun | Particle filter
pfilter-pfilterd_pomp | Particle filter
pfilter-pomp | Particle filter
pfilterd_pomp | Particle filter
pfilterd_pomp-class | Particle filter
plot | Plotting
plot-Abc | Plotting
plot-bsmcd_pomp | Plotting
plot-method | Plotting
plot-Mif2 | Plotting
plot-pfilterd_pomp | Plotting
plot-Pmcmc | Plotting
plot-pomp | Plotting
plot-probed_pomp | Plotting
plot-probe_match_objfun | Plotting
plot-spectd_pomp | Plotting
plot-spect_match_objfun | Plotting
pmcmc | The particle Markov chain Metropolis-Hastings algorithm
pmcmc-data.frame | The particle Markov chain Metropolis-Hastings algorithm
pmcmc-method | The particle Markov chain Metropolis-Hastings algorithm
pmcmc-pfilterd_pomp | The particle Markov chain Metropolis-Hastings algorithm
pmcmc-pmcmcd_pomp | The particle Markov chain Metropolis-Hastings algorithm
pmcmc-pomp | The particle Markov chain Metropolis-Hastings algorithm
pomp | Constructor of the basic pomp object
pomp,package | Inference for partially observed Markov processes
pred.mean | Prediction mean
pred.mean-kalmand_pomp | Prediction mean
pred.mean-method | Prediction mean
pred.mean-pfilterd_pomp | Prediction mean
pred.var | Prediction variance
pred.var-method | Prediction variance
pred.var-pfilterd_pomp | Prediction variance
print | Print methods
print-method | Print methods
prior_spec | prior specification
probe | Probes (AKA summary statistics)
probe-data.frame | Probes (AKA summary statistics)
probe-method | Probes (AKA summary statistics)
probe-objfun | Probes (AKA summary statistics)
probe-pomp | Probes (AKA summary statistics)
probe-probed_pomp | Probes (AKA summary statistics)
probe-probe_match_obfjun | Probes (AKA summary statistics)
probe.acf | Useful probes for partially-observed Markov processes
probe.ccf | Useful probes for partially-observed Markov processes
probe.marginal | Useful probes for partially-observed Markov processes
probe.match | Probe matching
probe.mean | Useful probes for partially-observed Markov processes
probe.median | Useful probes for partially-observed Markov processes
probe.nlar | Useful probes for partially-observed Markov processes
probe.period | Useful probes for partially-observed Markov processes
probe.quantile | Useful probes for partially-observed Markov processes
probe.sd | Useful probes for partially-observed Markov processes
probe.var | Useful probes for partially-observed Markov processes
probe_objfun | Probe matching
probe_objfun-data.frame | Probe matching
probe_objfun-method | Probe matching
probe_objfun-pomp | Probe matching
probe_objfun-probed_pomp | Probe matching
probe_objfun-probe_match_objfun | Probe matching
profileDesign | Design matrices for pomp calculations
proposals | MCMC proposal distributions

## -- R --

reulermultinom | Probability distributions
rgammawn | Probability distributions
ricker | Ricker model with Poisson observations.
rinit | rinit
rinit-method | rinit
rinit-pomp | rinit
rinit_spec | The initial-state distribution
rmeasure | rmeasure
rmeasure-method | rmeasure
rmeasure-pomp | rmeasure
rmeasure_spec | The measurement-model simulator
rprior | rprior
rprior-method | rprior
rprior-pomp | rprior
rprocess | rprocess
rprocess-method | rprocess
rprocess-pomp | rprocess
rprocess_spec | The latent state process simulator
runifDesign | Design matrices for pomp calculations
rw.sd | rw.sd
rw2 | Two-dimensional random-walk process

## -- S --

sannbox | Simulated annealing with box constraints.
simulate | Simulations of a partially-observed Markov process
simulate-data.frame | Simulations of a partially-observed Markov process
simulate-method | Simulations of a partially-observed Markov process
simulate-missing | Simulations of a partially-observed Markov process
simulate-objfun | Simulations of a partially-observed Markov process
simulate-pomp | Simulations of a partially-observed Markov process
sir | Compartmental epidemiological models
sir2 | Compartmental epidemiological models
sir_models | Compartmental epidemiological models
skeleton | skeleton
skeleton-method | skeleton
skeleton-pomp | skeleton
skeleton_spec | The deterministic skeleton of a model
sliceDesign | Design matrices for pomp calculations
sobolDesign | Design matrices for pomp calculations
spect | Power spectrum
spect-data.frame | Power spectrum
spect-method | Power spectrum
spect-objfun | Power spectrum
spect-pomp | Power spectrum
spect-spectd_pomp | Power spectrum
spect-spect_match_objfun | Power spectrum
spect.match | Spectrum matching
spect_objfun | Spectrum matching
spect_objfun-data.frame | Spectrum matching
spect_objfun-method | Spectrum matching
spect_objfun-pomp | Spectrum matching
spect_objfun-spectd_pomp | Spectrum matching
spect_objfun-spect_match_objfun | Spectrum matching
spy | Spy
spy-method | Spy
states | Latent states
states-method | Latent states
states-pomp | Latent states
stew | Bake, stew, and freeze
summary | Summary methods
summary-method | Summary methods
summary-objfun | Summary methods
summary-probed_pomp | Summary methods
summary-spectd_pomp | Summary methods

## -- T --

time | Methods to manipulate the obseration times
time-method | Methods to manipulate the obseration times
time-pomp | Methods to manipulate the obseration times
time<- | Methods to manipulate the obseration times
time<--method | Methods to manipulate the obseration times
time<--pomp | Methods to manipulate the obseration times
timezero | The zero time
timezero-method | The zero time
timezero-pomp | The zero time
timezero<- | The zero time
timezero<--method | The zero time
timezero<--pomp | The zero time
traces | Traces
traces-Abc | Traces
traces-abcd_pomp | Traces
traces-abcList | Traces
traces-method | Traces
traces-Mif2 | Traces
traces-mif2d_pomp | Traces
traces-mif2List | Traces
traces-Pmcmc | Traces
traces-pmcmcd_pomp | Traces
traces-pmcmcList | Traces
traj.match | Trajectory matching
trajectory | Trajectory of a deterministic model
trajectory-method | Trajectory of a deterministic model
trajectory-pomp | Trajectory of a deterministic model
trajectory-traj_match_objfun | Trajectory of a deterministic model
traj_objfun | Trajectory matching
traj_objfun-data.frame | Trajectory matching
traj_objfun-method | Trajectory matching
traj_objfun-pomp | Trajectory matching
traj_objfun-traj_match_objfun | Trajectory matching
transformations | Transformations

## -- U --

userdata | Facilities for making additional information to basic components

## -- V --

vectorfield | The deterministic skeleton of a model
verhulst | Verhulst-Pearl model

## -- W --

window | Window
window-method | Window
window-pomp | Window
workhorses | Workhorse functions for the 'pomp' algorithms.