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,thres,iter.max,my.alpha, ...)
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.