Learn R Programming

⚠️There's a newer version (6.3) of this package.Take me there.

pomp (version 0.45-8)

Statistical inference for partially observed Markov processes

Description

Inference methods for partially-observed Markov processes

Copy Link

Version

Install

install.packages('pomp')

Monthly Downloads

2,074

Version

0.45-8

License

GPL (>= 2)

Maintainer

Aaron King

Last Published

January 9th, 2014

Functions in pomp (0.45-8)

bsmc

Liu and West Bayesian Particle Filter
dacca

Model of cholera transmission for historic Bengal.
dprocess-pomp

Evaluate the probability density of state transitions in a Markov process
verhulst

Simple Verhulst-Pearl (logistic) model.
mif-methods

Methods of the "mif" class
sliceDesign

Design matrices for likelihood slices.
logmeanexp

The log-mean-exp trick
pomp-fun

Definition and methods of the "pomp.fun" class
B-splines

B-spline bases
LondonYorke

Historical childhood disease incidence data
pfilter

Particle filter
sannbox

Simulated annealing with box constraints.
ou2

Two-dimensional discrete-time Ornstein-Uhlenbeck process
gompertz

Gompertz model with log-normal observations.
dmeasure-pomp

Evaluate the probability density of observations given underlying states in a partially-observed Markov process
mif-class

The "mif" class
eulermultinom

Euler-multinomial death process
basic.probes

Some probes for partially-observed Markov processes
probe

Probe a partially-observed Markov process.
pompExample

Pre-built examples of pomp objects.
pompBuilder

Write, compile, link, and build a pomp object using native codes
nlf

Fit Model to Data Using Nonlinear Forecasting (NLF)
pomp-methods

Methods of the "pomp" class
simulate-pomp

Running simulations of a partially-observed Markov process
sobol

Sobol' low-discrepancy sequence
rmeasure-pomp

Simulate the measurement model of a partially-observed Markov process
profileDesign

Design matrices for likelihood profile calculations.
particles-mif

Generate particles from the user-specified distribution.
spect

Power spectrum computation for partially-observed Markov processes.
skeleton-pomp

Evaluate the deterministic skeleton at the given points in state space.
pomp-package

Partially-observed Markov processes
pomp-class

Partially-observed Markov process class
ricker

Ricker model with Poisson observations.
pfilter-methods

Methods of the "pfilterd.pomp" class
rprocess-pomp

Simulate the process model of a partially-observed Markov process
plugins

Plug-ins for dynamical models based on stochastic Euler algorithms
parmat

Create a matrix of parameters
traj.match

Trajectory matching
pomp

Partially-observed Markov process object.
mif

The MIF algorithm
pmcmc-methods

Methods of the "pmcmc" class
trajectory

Compute trajectories of the deterministic skeleton.
init.state-pomp

Return a matrix of initial conditions given a vector of parameters and an initial time.
sir

SIR models.
probed.pomp-methods

Methods of the "probed.pomp", "probe.matched.pomp", "spect.pomp", and "spect.matched.pomp" classes
rw2

Two-dimensional random-walk process
pmcmc

The PMCMC algorithm
blowflies

Model for Nicholson's blowflies.