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pomp (version 0.49-1)
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
1,709
Version
0.49-1
License
GPL (>= 2)
Maintainer
Aaron King
Last Published
March 23rd, 2014
Functions in pomp (0.49-1)
Search all functions
eulermultinom
Euler-multinomial death process
pfilter-methods
Methods of the "pfilterd.pomp" class
init.state-pomp
Return a matrix of initial conditions given a vector of parameters and an initial time.
verhulst
Simple Verhulst-Pearl (logistic) model.
pomp-class
Partially-observed Markov process class
mif-class
The "mif" class
parmat
Create a matrix of parameters
rprocess-pomp
Simulate the process model of a partially-observed Markov process
LondonYorke
Historical childhood disease incidence data
mif
The MIF algorithm
basic.probes
Some probes for partially-observed Markov processes
pompExample
Pre-built examples of pomp objects.
skeleton-pomp
Evaluate the deterministic skeleton at the given points in state space.
sobol
Sobol' low-discrepancy sequence
traj.match
Trajectory matching
pmcmc
The PMCMC algorithm
abc
The ABC algorithm
gompertz
Gompertz model with log-normal observations.
pomp-fun
Definition and methods of the "pomp.fun" class
sliceDesign
Design matrices for likelihood slices.
pfilter
Particle filter
particles-mif
Generate particles from the user-specified distribution.
dmeasure-pomp
Evaluate the probability density of observations given underlying states in a partially-observed Markov process
dprocess-pomp
Evaluate the probability density of state transitions in a Markov process
simulate-pomp
Running simulations of a partially-observed Markov process
blowflies
Model for Nicholson's blowflies.
pompBuilder
Write, compile, link, and build a pomp object using native codes
profileDesign
Design matrices for likelihood profile calculations.
pomp-methods
Methods of the "pomp" class
pomp-package
Partially-observed Markov processes
sir
SIR models.
nlf
Fit Model to Data Using Nonlinear Forecasting (NLF)
bsmc
Liu and West Bayesian Particle Filter
B-splines
B-spline bases
pmcmc-methods
Methods of the "pmcmc" class
ou2
Two-dimensional discrete-time Ornstein-Uhlenbeck process
abc-methods
Methods of the "abc" class
probe
Probe a partially-observed Markov process.
sannbox
Simulated annealing with box constraints.
pomp
Partially-observed Markov process object.
spect
Power spectrum computation for partially-observed Markov processes.
mif-methods
Methods of the "mif" class
plugins
Plug-ins for dynamical models based on stochastic Euler algorithms
rmeasure-pomp
Simulate the measurement model of a partially-observed Markov process
logmeanexp
The log-mean-exp trick
trajectory
Compute trajectories of the deterministic skeleton.
rw2
Two-dimensional random-walk process
dacca
Model of cholera transmission for historic Bengal.
prior-pomp
Evaluate or simulate from the prior probability density
probed.pomp-methods
Methods of the "probed.pomp", "probe.matched.pomp", "spect.pomp", and "spect.matched.pomp" classes
ricker
Ricker model with Poisson observations.