mstep: Maximisation step for Expectation-Maximisation algorithm
In markajoc/MBCbigP: Model-Based Clustering for High-Dimensional Data
Description
Usage
Arguments
Value
Description
Maximisation step for Expectation-Maximisation algorithm
Usage
1
Arguments
x
A matrix of data.
z
A matrix of cluster memberships/probabilities.
groups
Optional, number of groups in the mixture, inferred from
z if not supplied.
p
Optional, dimension of x, inferred from x if not
supplied
Value
A list of parameter estimates for the mixing proportions, mean
vectors, and covariance matrices.
markajoc/MBCbigP documentation built on May 30, 2019, 8:39 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
Description
Maximisation step for Expectation-Maximisation algorithm
Usage
1 |
Arguments
x |
A matrix of data. |
z |
A matrix of cluster memberships/probabilities. |
groups |
Optional, number of groups in the mixture, inferred from
|
p |
Optional, dimension of |
Value
A list of parameter estimates for the mixing proportions, mean vectors, and covariance matrices.
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.