DpmmGibbs: Gibbs sampling for the Gaussian Dirichlet process mixture...
In jlin-vt/SML: Statistical Machine Learning
Description
Usage
Arguments
Value
View source: R/gibbs_crp_gmm1d.R
Description
Gibbs sampling for the Gaussian Dirichlet process mixture model.
Usage
1
DpmmGibbs(x, alpha, tau0, beta0, mu0, kappa0, nIter)
Arguments
x
data (vector of length N).
alpha
DP concentration parameter.
tau0
normal-gamma prior shape.
beta0
normal-gamma prior rate (inverse scale).
kappa0
normal-gamma prior precision scaling parameter.
nIter
number of Gibbs iterations.
Value
C N x nIter matrix of cluster assignments.
jlin-vt/SML documentation built on Dec. 5, 2019, 2:05 a.m.
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.
Description Usage Arguments Value
View source: R/gibbs_crp_gmm1d.R
Description
Gibbs sampling for the Gaussian Dirichlet process mixture model.
Usage
1 | DpmmGibbs(x, alpha, tau0, beta0, mu0, kappa0, nIter)
|
Arguments
x |
data (vector of length N). |
alpha |
DP concentration parameter. |
tau0 |
normal-gamma prior shape. |
beta0 |
normal-gamma prior rate (inverse scale). |
kappa0 |
normal-gamma prior precision scaling parameter. |
nIter |
number of Gibbs iterations. |
Value
C N x nIter matrix of cluster assignments.
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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.