Description: Tools for working with partially observed Markov process (POMP) models (also known as stochastic dynamical systems, hidden Markov models, and nonlinear, non-Gaussian, state-space models).  The package provides facilities for implementing POMP models, simulating them, and fitting them to time series data by a variety of frequentist and Bayesian methods.  It is also a versatile platform for implementation of inference methods for general POMP models.
safecall.R pomp_fun.R plugins.R builder.R parmat.R logmeanexp.R
slice_design.R profile_design.R sobol.R bsplines.R sannbox.R
pomp_class.R load.R pomp.R pomp_methods.R rmeasure_pomp.R
pfilter_methods.R minim.R traj_match.R bsmc.R bsmc2.R kalman.R
kalman_methods.R mif.R mif_methods.R mif2.R mif2_methods.R
proposals.R pmcmc.R pmcmc_methods.R nlf_funcs.R nlf_guts.R
nlf_objfun.R nlf.R probe.R probe_match.R basic_probes.R spect.R
spect_match.R abc.R abc_methods.R covmat.R example.R

safecall.R pomp_fun.R plugins.R templates.R builder.R parmat.R
logmeanexp.R slice_design.R profile_design.R sobol.R bsplines.R
sannbox.R pomp_class.R load.R pomp.R pomp_methods.R
pfilter.R pfilter_methods.R minim.R traj_match.R bsmc.R bsmc2.R
kalman.R kalman_methods.R mif.R mif_methods.R mif2.R
mif2_methods.R proposals.R pmcmc.R pmcmc_methods.R nlf_funcs.R
nlf_guts.R nlf_objfun.R nlf.R probe.R probe_match.R
basic_probes.R spect.R spect_match.R abc.R abc_methods.R

pomp_fun.R plugins.R builder.R parmat.R logmeanexp.R
pfilter_methods.R minim.R traj_match.R bsmc.R bsmc2.R mif.R
mif_methods.R mif2.R mif2_methods.R proposals.R pmcmc.R
pmcmc_methods.R nlf_funcs.R nlf_guts.R nlf_objfun.R nlf.R
probe.R probe_match.R basic_probes.R spect.R spect_match.R

Description: Tools for data analysis with partially observed Markov process (POMP) models (also known as stochastic dynamical systems, hidden Markov models, and nonlinear, non-Gaussian, state-space models).  The package provides facilities for implementing POMP models, simulating them, and fitting them to time series data by a variety of frequentist and Bayesian methods.  It is also a versatile platform for implementation of inference methods for general POMP models.
Imports: stats, graphics, digest, mvtnorm, deSolve, coda, reshape2,
Suggests: ggplot2, knitr, tidyr, dplyr, subplex
Collate: 'pomp-package.R' 'aaa.R' 'pstop.R' 'undefined.R' 'csnippet.R'
'rinit_spec.R' 'templates.R' 'builder.R' 'pomp.R' 'probe.R'
'abc.R' 'accumulators.R' 'kalman.R' 'proposals.R' 'pfilter.R'
'pmcmc.R' 'mif2.R' 'listie.R' 'simulate.R' 'spect.R' 'plot.R'
'bsmc2.R' 'as_data_frame.R' 'as_pomp.R' 'authors.R' 'bake.R'
'basic_probes.R' 'blowflies.R' 'bsflu.R' 'bsplines.R' 'coef.R'
'concat.R' 'cond_logLik.R' 'covmat.R' 'dacca.R' 'traces.R'
'traj_match.R' 'objfun.R' 'loglik.R' 'logmeanexp.R' 'lookup.R'
'measles.R' 'melt.R' 'obs.R' 'ou2.R' 'parmat.R' 'parus.R'
'pipe.R' 'pred_mean.R' 'pred_var.R' 'show.R' 'print.R'
'rw2.R' 'sannbox.R' 'sir.R' 'slice_design.R' 'sobol.R' 'spy.R'