bpfPMMH: Boostrap Particle Filter for the toy SV model
In ilyaZar/SVmodelRcppSMC: RcppSMC package example for the Stochastic volatitly model
Description
Usage
Arguments
Value
Description
Computes, besides other things, an estimate of the log-likelihood.
Usage
1
bpfPMMH(NN, yt, phiX, sigmaX, betaY)
Arguments
NN
number of particles
yt
measurements/data of the unobservered latent state process
phiX
phi parameter (see model equations for details)
sigmaX
sigma parameter (see model equations for details)
betaY
beta parameter (see model equations for details)
Value
a list of one element (was previously returniong more) giving the
log-likelihood estimate
ilyaZar/SVmodelRcppSMC documentation built on Dec. 20, 2021, 6:57 p.m.
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Description Usage Arguments Value
Description
Computes, besides other things, an estimate of the log-likelihood.
Usage
1 | bpfPMMH(NN, yt, phiX, sigmaX, betaY)
|
Arguments
NN |
number of particles |
yt |
measurements/data of the unobservered latent state process |
phiX |
phi parameter (see model equations for details) |
sigmaX |
sigma parameter (see model equations for details) |
betaY |
beta parameter (see model equations for details) |
Value
a list of one element (was previously returniong more) giving the log-likelihood estimate
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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