R: Point estimate of the partition using a modified Binder loss...

cluster_est_Mbinder_norm {NPflow} | R Documentation

## Point estimate of the partition using a modified Binder loss function

### Description

Get a point estimate of the partition using a modified Binder loss function for Gaussian components

### Usage

    cluster_est_Mbinder_norm(c, Mu, Sigma, lambda = 0, a = 1, b = a, logposterior)

### Arguments

`c` | a list of vector of length `n`. `c[[j]][i]` is the cluster allocation of observation `i=1...n` at iteration `j=1...N`.
`Mu` | is a list of length `n` composed of `p x l` matrices. Where `l` is the maximum number of components per partition.
`Sigma` | is list of length `n` composed of arrays containing a maximum of `l` `p x p` covariance matrices.
`lambda` | is a nonnegative tunning parameter allowing further control over the distance function. Default is 0.
`a` | nonnegative constant seen as the unit cost for pairwise misclassification. Default is 1.
`b` | nonnegative constant seen as the unit cost for the other kind of pairwise misclassification. Default is 1.
`logposterior` | vector of logposterior corresponding to each partition from `c` used to break ties when minimizing the cost function

### Details

Note that he current implementation only allows Gaussian components.

The modified Binder loss function takes into account the distance between mixture components using #'the Bhattacharyya distance.

### Value

a `list`:

- `c_est`: a vector of length `n`. Point estimate of the partition

- `cost`: a vector of length `N`. `cost[j]` is the cost associated to partition `c[[j]]`

- `similarity`: matrix of size `n x n`. Similarity matrix (see `similarityMat`)

- `opt_ind`: the index of the optimal partition among the MCMC iterations.

### Author(s)

Chariff Alkhassim

### References

JW Lau, PJ Green, Bayesian Model-Based Clustering Procedures, Journal of Computational and Graphical Statistics, 16(3):526-558, 2007.

DA Binder, Bayesian cluster analysis, Biometrika 65(1):31-38, 1978.

### See Also

`similarityMat` `similarityMatC` `similarityMat_nocostC`

[Package NPflow version 0.13.3 Index]