gibbsGMM: Fit a mixture of Gaussians to the observed data.
In bayesImageS: Bayesian Methods for Image Segmentation using a Potts Model
Description
Usage
Arguments
Value
Description
Fit a mixture of Gaussians to the observed data.
Usage
1
Arguments
y
A vector of observed pixel data.
niter
The number of iterations of the algorithm to perform.
nburn
The number of iterations to discard as burn-in.
priors
A list of priors for the parameters of the model.
Value
A matrix containing MCMC samples for the parameters of the mixture model.
bayesImageS documentation built on April 11, 2021, 5:06 p.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
Description
Fit a mixture of Gaussians to the observed data.
Usage
1 |
Arguments
y |
A vector of observed pixel data. |
niter |
The number of iterations of the algorithm to perform. |
nburn |
The number of iterations to discard as burn-in. |
priors |
A list of priors for the parameters of the model. |
Value
A matrix containing MCMC samples for the parameters of the mixture model.
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.