MFclust.compute {MFDA} | R Documentation |
The computation componenet for clustering via rejection-controlled EM initialized by kmeans clustering for functional Gaussian mixture models. The number of clusters and the clustering model is chosen to minimize the BIC.
MFclust.compute(data, minG, maxG, nchain=NULL,thres=NULL,iter.max=NULL,my.alpha=NULL, ...)
data |
A numeric vector, matrix, or data frame of observations. Categorical variables are not allowed. If a matrix or data frame, rows correspond to observations and columns correspond to time. |
minG |
An integer vector specifying the minimum number of mixture components
(clusters) to be considered.
The default is 1 component.
|
maxG |
An integer vector specifying the maximum number of mixture components
(clusters) to be considered.
The default is 9 components.
|
nchain |
An integer specifying the number of Markov chains in RCEM
The default is 5 chains.
|
thres |
A number between 0 and 1 specifying the threshold value of rejection step in RCEM.
The default is 0.5 .
|
iter.max |
An iteger specifying the maximum number of iteration in RCEM.
The default is 10 .
|
my.alpha |
The prior for the cluster proportion.
The default is 1 .
|
... |
The arguments to be part of the function. |
A list representing the best model (according to BIC) for the given range of numbers of clusters.
Ma, P., Castillo-Davis, C., Zhong, W., and Liu, J. S. (2006) A data-driven clustering method for time course gene expression data, Nucleic Acids Research, 34 (4), 1261-1269.