Provided to allow lists with elements other than the arguments can
 be passed in indirect or list calls with <code>do.call</code>.

Converts a matrix in which each row sums to 1 
 into the nearest matrix of (0,1) indicator variables. Borrowed from the mclust package, used as internal function.

cluster

The package supplies two efficients methodologies:
        regularized CCA and sparse PLS to unravel relationships between
        two heterogeneous data sets of size (nxp) and (nxq) where the p
        and q variables are measured on the same samples or individuals
        n. These data may come from high throughput technologies, such
        as omics data (e.g. transcriptomics, metabolomics or proteomics
        data) that require an integrative or joint analysis. However,
        mixOmics can also be applied to any other large data sets where
        p + q >> n. rCCA is a regularized version of CCA to deal with
        the large number of variables. sPLS allows variable selection
        in a one step procedure and two frameworks are proposed:
        regression and canonical analysis. Numerous graphical outputs
        are provided to help interpreting the results.

Kim-Anh Cao

mixOmics

Integrate Omics data project

map function

encoding

C. Fraley and A. E. Raftery (2002).
 Model-based clustering, discriminant analysis, and density estimation.
 Journal of the American Statistical Association 97:611-631. 

 C. Fraley and A. E. Raftery (2006).
 MCLUST Version 3 for R: Normal Mixture Modeling and Model-Based Clustering, 
 Technical Report no. 504, Department of Statistics,
 University of Washington.

map: Converts an indicator matrix to class vector

Description

Usage

Arguments

Value

encoding

References

See Also