z_ig_random_hard: Random Hard Initialization

In mixture: Mixture Models for Clustering and Classification

Random Hard Initialization

Description

Generates an initialization matrix of size n times g using random hard.

Usage

z_ig_random_hard(n,g)

Arguments

n	Number of rows, must be positive.
g	Number of columns, must be positive.

Author(s)

Nik Pocuca, Ryan P. Browne and Paul D. McNicholas.

Maintainer: Paul D. McNicholas <[e-mail]>

References

Browne, R.P. and McNicholas, P.D. (2014). Estimating common principal components in high dimensions. Advances in Data Analysis and Classification 8(2), 217-226.

Zhou, H. and Lange, K. (2010). On the bumpy road to the dominant mode. Scandinavian Journal of Statistics 37, 612-631.

Celeux, G., Govaert, G. (1995). Gaussian parsimonious clustering models. Pattern Recognition 28(5), 781-793.

Examples

z_init <- z_ig_random_hard(100,3)

mixture documentation built on May 29, 2024, 1:47 a.m.