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pomp (version 0.53-1)
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
2,074
Version
0.53-1
License
GPL (>= 2)
Maintainer
Aaron King
Last Published
June 30th, 2014
Functions in pomp (0.53-1)
Search all functions
ou2
Two-dimensional discrete-time Ornstein-Uhlenbeck process
skeleton-pomp
Evaluate the deterministic skeleton at the given points in state space.
sliceDesign
Design matrices for likelihood slices.
rprocess-pomp
Simulate the process model of a partially-observed Markov process
mif-methods
Methods of the "mif" class
mif
Iterated filtering
pfilter-methods
Methods of the "pfilterd.pomp" class
dmeasure-pomp
Evaluate the probability density of observations given underlying states in a partially-observed Markov process
LondonYorke
Historical childhood disease incidence data
rw2
Two-dimensional random-walk process
eulermultinom
Euler-multinomial death process
nlf
Fit Model to Data Using Nonlinear Forecasting (NLF)
basic.probes
Some probes for partially-observed Markov processes
pomp-methods
Methods of the "pomp" class
gompertz
Gompertz model with log-normal observations.
abc
The ABC algorithm
dacca
Model of cholera transmission for historic Bengal.
blowflies
Model for Nicholson's blowflies.
B-splines
B-spline bases
pfilter
Particle filter
pompExample
Pre-built examples of pomp objects.
plugins
Plug-ins for dynamical models based on stochastic Euler algorithms
pmcmc
The PMCMC algorithm
pmcmc-methods
Methods of the "pmcmc" class
logmeanexp
The log-mean-exp trick
init.state-pomp
Return a matrix of initial conditions given a vector of parameters and an initial time.
pomp-fun
Definition and methods of the "pomp.fun" class
abc-methods
Methods of the "abc" class
dprocess-pomp
Evaluate the probability density of state transitions in a Markov process
pompBuilder
Write, compile, link, and build a pomp object using native codes
parmat
Create a matrix of parameters
Csnippet
C code snippets
sobol
Sobol' low-discrepancy sequence
spect
Power spectrum computation for partially-observed Markov processes.
profileDesign
Design matrices for likelihood profile calculations.
trajectory
Compute trajectories of the deterministic skeleton.
rmeasure-pomp
Simulate the measurement model of a partially-observed Markov process
probed.pomp-methods
Methods of the "probed.pomp", "probe.matched.pomp", "spect.pomp", and "spect.matched.pomp" classes
bsmc
Liu and West Bayesian Particle Filter
pomp-package
Partially-observed Markov processes
ricker
Ricker model with Poisson observations.
verhulst
Simple Verhulst-Pearl (logistic) model.
particles-mif
Generate particles from the user-specified distribution.
prior-pomp
Evaluate or simulate from the prior probability density
sir
SIR models.
simulate-pomp
Running simulations of a partially-observed Markov process
traj.match
Trajectory matching
pomp
Partially-observed Markov process object.
probe
Probe a partially-observed Markov process.
sannbox
Simulated annealing with box constraints.