Man pages for kidusasfaw/pomp
Statistical Inference for Partially Observed Markov Processes
| abc | Approximate Bayesian computation |
| accumulators | accumulators |
| as_data_frame | Coerce to data frame |
| as_pomp | as.pomp |
| bake | Bake, stew, and freeze |
| basic_probes | Useful probes for partially-observed Markov processes |
| blowflies | Nicholson's blowflies. |
| bsflu | Influenza outbreak in a boarding school |
| bsmc2 | The Liu and West Bayesian particle filter |
| bsplines | B-spline bases |
| coef | Extract, set, or alter coefficients |
| 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. |
| deprecated | Deprecated functions |
| design | Design matrices for pomp calculations |
| distributions | Probability distributions |
| dmeasure | dmeasure |
| dmeasure_spec | The measurement model density |
| dprior | dprior |
| dprocess | dprocess |
| dprocess_spec | The latent state process density |
| eff_sample_size | Effective sample size |
| filter_mean | Filtering mean |
| filter_traj | Filtering trajectories |
| 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 |
| listie | listie |
| load | Loading and unloading shared-object libraries |
| loglik | Log likelihood |
| logmeanexp | The log-mean-exp trick |
| lookup | Lookup table |
| measles | Historical childhood disease incidence data |
| 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 |
| parus | Parus major population dynamics |
| pfilter | Particle filter |
| plot | Plotting |
| pmcmc | The particle Markov chain Metropolis-Hastings algorithm |
| pomp | Constructor of the basic pomp object |
| pomp2-package | Inference for partially observed Markov processes |
| pomp_class | The basic pomp class |
| pomp_fun | The "pomp_fun" class |
| 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 |
| reexports | Objects exported from other packages |
| resample | Resample |
| ricker | Ricker model with Poisson observations. |
| rinit | rinit |
| rinit_spec | The initial-state distribution |
| rmeasure | rmeasure |
| rmeasure_spec | The measurement-model simulator |
| rprior | rprior |
| rprocess | rprocess |
| rprocess_spec | The latent state process simulator |
| rw2 | Two-dimensional random-walk process |
| rw_sd | rw.sd |
| sannbox | Simulated annealing with box constraints. |
| show | Show methods |
| simulate | Simulations of a partially-observed Markov process |
| sir | Compartmental epidemiological models |
| skeleton | skeleton |
| skeleton_spec | The deterministic skeleton of a model |
| spect | Power spectrum |
| spect_match | Spectrum matching |
| spy | Spy |
| states | Latent states |
| summary | Summary methods |
| time | Methods to 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 |
| window | Window |
| workhorses | Workhorse functions for the 'pomp' algorithms. |
