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pomp (version 0.37-1)
Statistical inference for partially observed Markov processes
Description
Inference methods for partially-observed Markov processes
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Install
install.packages('pomp')
Monthly Downloads
1,578
Version
0.37-1
License
GPL (>= 2)
Maintainer
Aaron King
Last Published
May 15th, 2011
Functions in pomp (0.37-1)
Search all functions
pomp-package
Partially-observed Markov processes
sobol
Sobol' low-discrepancy sequence
skeleton-pomp
Evaluate the deterministic skeleton at the given points in state space.
probed.pomp-methods
Methods of the "probed.pomp", "probe.matched.pomp", "spect.pomp", and "spect.matched.pomp" classes
ou2
Two-dimensional Ornstein-Uhlenbeck process
dmeasure-pomp
Evaluate the probability density of observations given underlying states in a partially-observed Markov process
simulate-pomp
Running simulations of a partially-observed Markov process
spect
Power spectrum computation for partially-observed Markov processes.
dprocess-pomp
Evaluate the probability density of state transitions in a Markov process
pmcmc-methods
Methods of the "pmcmc" class
dacca
Model of cholera transmission for historic Bengal.
mif
The MIF algorithm
pfilter
Particle filter
LondonYorke
Historical childhood disease incidence data
pomp
Partially-observed Markov process object.
mif-methods
Methods of the "mif" class
bsmc
Liu and West Bayesian Particle Filter
pmcmc
The PMCMC algorithm
rmeasure-pomp
Simulate the measurement model of a partially-observed Markov process
nlf
Fit Model to Data Using Nonlinear Forecasting (NLF)
Euler-multinomial models
Euler-multinomial models
rw2
Two-dimensional random-walk process
mif-class
The "mif" class
slice.design
Design matrices for likelihood slices.
pomp-class
Partially-observed Markov process class
probe
Probe a partially-observed Markov process.
B-splines
B-spline bases
pomp-fun
Definition and methods of the "pomp.fun" class
pfilter-methods
Methods of the "pfilterd.pomp" class
gompertz
Gompertz model with normal observations.
basic.probes
Some probes for partially-observed Markov processes
blowflies
Model for Nicholson's blowflies.
particles-mif
Generate particles from the user-specified distribution.
init.state-pomp
Return a matrix of initial conditions given a vector of parameters and an initial time.
plugins
Plug-ins for dynamical models based on stochastic Euler algorithms
trajectory
Compute trajectories of the determinstic skeleton.
ricker
Ricker model with Poisson observations.
profile.design
Design matrices for likelihood profile calculations.
verhulst
Simple Verhulst-Pearl (logistic) model.
pomp-methods
Methods of the "pomp" class
rprocess-pomp
Simulate the process model of a partially-observed Markov process
sir
Seasonal SIR model implemented using two stochastic simulation algorithms.
traj.match
Trajectory matching