Man pages for pomp
Statistical Inference for Partially Observed Markov Processes
| abc | Approximate Bayesian computation |
| accumvars | accumulator variables |
| as_data_frame | Coerce to data frame |
| as_pomp | as.pomp |
| bake | Tools for reproducible computations |
| basic_components | Basic POMP model components. |
| basic_probes | Useful probes for partially-observed Markov processes |
| betabinom | Beta-binomial distribution |
| blowflies | Nicholson's blowflies. |
| bsflu | Influenza outbreak in a boarding school |
| bsmc2 | The Liu and West Bayesian particle filter |
| bsplines | B-spline bases |
| childhood | Historical childhood disease incidence data |
| coef | Extract, set, or alter coefficients |
| conc | Concatenate |
| concat | Concatenate |
| cond_logLik | Conditional log likelihood |
| continue | Continue an iterative calculation |
| covariate_table | Covariates |
| covmat | Estimate a covariance matrix from algorithm traces |
| csnippet | C snippets |
| dacca | Model of cholera transmission for historic Bengal. |
| design | Design matrices for pomp calculations |
| dinit | dinit workhorse |
| dinit_spec | dinit specification |
| dmeasure | dmeasure workhorse |
| dmeasure_spec | dmeasure specification |
| dprior | dprior workhorse |
| dprocess | dprocess workhorse |
| dprocess_spec | dprocess specification |
| ebola | Ebola outbreak, West Africa, 2014-2016 |
| eff_sample_size | Effective sample size |
| elementary_algorithms | Elementary computations on POMP models. |
| emeasure | emeasure workhorse |
| emeasure_spec | emeasure specification |
| estimation_algorithms | Parameter estimation algorithms for POMP models. |
| eulermultinom | Eulermultinomial and gamma-whitenoise distributions |
| filter_mean | Filtering mean |
| filter_traj | Filtering trajectories |
| flow | flow workhorse |
| forecast | Forecast mean |
| gompertz | Gompertz model with log-normal observations. |
| hitch | Hitching C snippets and R functions to pomp_fun objects |
| kalman | Ensemble Kalman filters |
| kf | Kalman filter |
| listie | listie |
| load | Loading and unloading shared-object libraries |
| loglik | Log likelihood |
| logmeanexp | The log-mean-exp trick |
| lookup | Lookup table |
| mcap | Monte Carlo adjusted profile |
| melt | Melt |
| mif2 | Iterated filtering: maximum likelihood by iterated, perturbed... |
| nlf | Nonlinear forecasting |
| objfun | Objective functions |
| obs | obs |
| ou2 | Two-dimensional discrete-time Ornstein-Uhlenbeck process |
| parameter_trans | parameter transformations |
| parmat | Create a matrix of parameters |
| partrans | partrans workhorse |
| parus | Parus major population dynamics |
| pfilter | Particle filter |
| plot | pomp plotting facilities |
| pmcmc | The particle Markov chain Metropolis-Hastings algorithm |
| pomp | Constructor of the basic pomp object |
| pomp_class | The basic pomp class |
| pomp_examp | pre-built pomp examples |
| pomp_fun | The "pomp_fun" class |
| pomp-package | Inference for partially observed Markov processes |
| pred_mean | Prediction mean |
| pred_var | Prediction variance |
| Print methods | |
| prior_spec | prior specification |
| probe | Probes (AKA summary statistics) |
| probe_match | Probe matching |
| proposals | MCMC proposal distributions |
| pStop | pStop, pWarn, pMess |
| resample | Resample |
| ricker | Ricker model with Poisson observations. |
| rinit | rinit workhorse |
| rinit_spec | rinit specification |
| rmeasure | rmeasure workhorse |
| rmeasure_spec | rmeasure specification |
| rprior | rprior workhorse |
| rprocess | rprocess workhorse |
| rprocess_spec | rprocess specification |
| rw2 | Two-dimensional random-walk process |
| rw_sd | rw_sd |
| sannbox | Simulated annealing with box constraints. |
| saved_states | Saved states |
| show | Show methods |
| simulate | Simulations of a partially-observed Markov process |
| sir | Compartmental epidemiological models |
| skeleton | skeleton workhorse |
| skeleton_spec | skeleton specification |
| spect | Power spectrum |
| spect_match | Spectrum matching |
| spy | Spy |
| states | Latent states |
| summary | Summary methods |
| time | Methods to extract and manipulate the obseration times |
| timezero | The zero time |
| traces | Traces |
| trajectory | Trajectory of a deterministic model |
| traj_match | Trajectory matching |
| transformations | Transformations |
| undefined | Undefined |
| userdata | Facilities for making additional information to basic... |
| verhulst | Verhulst-Pearl model |
| vmeasure | vmeasure workhorse |
| vmeasure_spec | vmeasure specification |
| window | Window |
| workhorses | Workhorse functions for the 'pomp' algorithms. |
| wpfilter | Weighted particle filter |
| wquant | Weighted quantile function |
