c(person(given=c("Aaron","A."),family="King",
role=c("aut","cre"),email="kingaa@umich.edu"),
person(given=c("Edward","L."),family="Ionides",role=c("aut")),
person(given=c("Carles"),family="Breto",role=c("aut")),
person(given=c("Stephen","P."),family="Ellner",role=c("ctb")),
person(given=c("Matthew","J."),family="Ferrari",role=c("ctb")),
person(given=c("Bruce","E."),family="Kendall",role=c("ctb")),
person(given=c("Michael"),family="Lavine",role=c("ctb")),
person(given="Dao",family="Nguyen",role=c("ctb")),
person(given=c("Daniel","C."),family="Reuman",role=c("ctb")),
person(given=c("Helen"),family="Wearing",role=c("ctb")),
person(given=c("Simon","N."),family="Wood",role=c("ctb")),
person(given="Sebastian",family="Funk",role=c("ctb")),
person(given=c("Steven","G."),family="Johnson",role=c("ctb"))
)
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.
aaa.R authors.R bake.R generics.R eulermultinom.R csnippet.R
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
rprocess_pomp.R initstate_pomp.R dmeasure_pomp.R
dprocess_pomp.R skeleton_pomp.R dprior_pomp.R rprior_pomp.R
simulate_pomp.R trajectory_pomp.R plot_pomp.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 covmat.R example.R
Aaron A. King [aut, cre],
Edward L. Ionides [aut],
Carles Breto [aut],
Stephen P. Ellner [ctb],
Matthew J. Ferrari [ctb],
Bruce E. Kendall [ctb],
Michael Lavine [ctb],
Dao Nguyen [ctb],
Daniel C. Reuman [ctb],
Helen Wearing [ctb],
Simon N. Wood [ctb],
Sebastian Funk [ctb],
Steven G. Johnson [ctb]