SirLinearGauss: SMC method using SIR algorithm in linear Gaussian state-space...
In jlin-vt/SML: Statistical Machine Learning
Description
Usage
Arguments
Value
View source: R/sir_linear_gauss.R
Description
SMC method using SIR algorithm in linear Gaussian state-space model.
Usage
1
SirLinearGauss(y, T, N, S.v, S.w, phi)
Arguments
y
obeservations.
T
time.
N
size.
S.v
noise.
S.w
noise.
phi
scale parameter.
Value
a list of objects:
mu.Xs mean sample.
var.Xs variance sample.
jlin-vt/SML documentation built on Dec. 5, 2019, 2:05 a.m.
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Description Usage Arguments Value
View source: R/sir_linear_gauss.R
Description
SMC method using SIR algorithm in linear Gaussian state-space model.
Usage
1 | SirLinearGauss(y, T, N, S.v, S.w, phi)
|
Arguments
y |
obeservations. |
T |
time. |
N |
size. |
S.v |
noise. |
S.w |
noise. |
phi |
scale parameter. |
Value
a list of objects: mu.Xs mean sample. var.Xs variance sample.
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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