| Title: | Model-Based Clustering via Mixtures of Unrestricted Skew-t Sactor Analyzer Models |
|---|---|
| Description: | Implements mixtures of unrestricted skew-t factor analyzer models via the EM algorithm. |
| Authors: | Paula M. Murray, Ryan P. Browne, and Paul D. McNicholas |
| Maintainer: | Paula M. Murray <[email protected]> |
| License: | GPL (>= 2) |
| Version: | 2.0 |
| Built: | 2024-11-28 06:34:10 UTC |
| Source: | CRAN |
This package contains measurements on 200 Swiss banknotes: 100 genuine and 100 counterfeit. The variables are length of bill, width of left edge, width of right edge , bottom margin width and top margin width. All measurements are in millimetres. The data source is noted below. This data is also available in the alr package in R.
data(banknote)data(banknote)
Flury, B. and Riedwyl, H. (1988). Multivariate Statistics: A practical approach. London: Chapman and Hall.
data(banknote) # Loads the brown bread data set head(banknote) # Displays the first six rows of the brown bread data setdata(banknote) # Loads the brown bread data set head(banknote) # Displays the first six rows of the brown bread data set
Fits a mixture of 'unrestricted' skew-t factor analyzers via the EM algorithm for estimation of model parameters
uskewFA(x, G, q, init=1, max.it=100)uskewFA(x, G, q, init=1, max.it=100)
x |
A numeric matrix. |
G |
The number of mixture components to fit. |
q |
The number of latent factors. |
init |
This number controls the starting values that are used: (1) k-means, or (2) random. |
max.it |
The maximum number of iterations of the EM algorithm. |
map |
A vector of the maximum a posteriori group memberships. |
bic |
The value of the Bayesian Information Criterion. |
zhat |
The matrix of estimated probabilities of group membership. |
likelihood |
A vector containing the value of the complete-data log-likelihood computed at each iteration of the EM algorithm. |
This package contains measurements on 200 Swiss banknotes: 100 genuine and 100 counterfeit. The variables are length of bill, width of left edge, width of right edge , bottom margin width and top margin width. All measurements are in millimetres. The data source is noted below.
Paula M. Murray, Ryan P. Browne, and Paul D. McNicholas
Maintainer: Paula M. Murray <[email protected]>
Murray, P.M., Browne, R.P., and McNicholas, P.D. (2014), "Mixtures of 'Unrestricted' Skew-t Factor Analyzers". Arxiv preprint arXiv:1310.6224
Flury, B. and Riedwyl, H. (1988). Multivariate Statistics: A practical approach. London: Chapman and Hall.
data("banknote") x=banknote[,c(5,6)] # We let max.it=3 for a speedy illustration. # More iterations are needed to ensure # convergence. results=uskewFA(x,G=2,q=1,max.it=3) resultsdata("banknote") x=banknote[,c(5,6)] # We let max.it=3 for a speedy illustration. # More iterations are needed to ensure # convergence. results=uskewFA(x,G=2,q=1,max.it=3) results
Contains the function uskewFA for fitting mixtures of 'unrestricted' skew-t factor analyzer models
| Package: | uskewFactors |
| Type: | Package |
| Version: | 2.0 |
| Date: | 2016-05-20 |
| License: | WGPL (>=2) |
Paula M. Murray, Ryan P. Browne, and Paul D. McNicholas
Maintainer: Paula M. Murray <[email protected]>
Murray, P.M., Browne, R.P., and McNicholas, P.D. (2014), "Mixtures of 'Unrestricted' Skew-t Factor Analyzers". Arxiv preprint arXiv:1310.6224
Details, references, and examples are given under uskewFA.