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pomp (version 0.28-2)
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
1,238
Version
0.28-2
License
GPL (>= 2)
Maintainer
Aaron King
Last Published
March 23rd, 2010
Functions in pomp (0.28-2)
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LondonYorke
Reported cases of chickenpox, measles, and mumps from Baltimore and New York, 1928--1972
B-splines
B-spline bases
dprocess-pomp
Evaluate the probability density of state transitions in a Markov process
euler
Plug-ins for dynamical models based on stochastic Euler algorithms
dmeasure-pomp
Evaluate the probability density of observations given underlying states in a partially-observed Markov process
init.state-pomp
Return a matrix of initial conditions given a vector of parameters and an initial time.
mif-class
The "mif" class
euler.sir
Seasonal SIR model implemented as an Euler-multinomial model
mif-methods
Methods of the "mif" class
Euler-multinomial models
Euler-multinomial models
mif
The MIF algorithm
nlf
Fit Model to Data Using Nonlinear Forecasting (NLF)
ou2
Two-dimensional Ornstein-Uhlenbeck process
pfilter
Particle filter
particles-mif
Generate particles from the user-specified distribution.
pomp-class
Partially-observed Markov process
pomp-package
Partially-observed Markov processes
pomp-methods
Methods of the "pomp" class
rw2
Two-dimensional random-walk process
rprocess-pomp
Simulate the process model of a partially-observed Markov process
pomp
Partially-observed Markov process object.
rmeasure-pomp
Simulate the measurement model of a partially-observed Markov process
skeleton-pomp
Evaluate the deterministic skeleton at the given points in state space.
simulate-pomp
Running simulations of a partially-observed Markov process
slice.design
Design matrices for likelihood slices and profiles
verhulst
Simple Verhulst-Pearl (logistic) model.
trajectory-pomp
Compute trajectories of the determinstic skeleton.
traj.match
Trajectory matching
sobol
Sobol' low-discrepancy sequence