Description Usage Arguments Value Note Author(s) References See Also Examples
Between class coinertia analysis. cia
of 2 datasets where
covariance between groups or classes of cases, rather than individual cases are maximised.
1 | bet.coinertia(df1, df2, fac1, fac2, cia.nf = 2, type = "nsc", ...)
|
df1 |
First dataset.A |
df2 |
Second dataset. A |
fac1 |
A |
fac2 |
A |
cia.nf |
Integer indicating the number of coinertia analysis axes to be saved. Default value is 2. |
type |
A character string, accepted options are type="nsc" or type="pca". |
... |
further arguments passed to or from other methods. |
A list of class bet.cia
of length 5
coin |
An object of class 'coinertia', sub-class |
coa1, pca1 |
An object of class 'nsc' or 'pca', with sub-class
'dudi'. See |
coa2, pca2 |
An object of class 'nsc' or 'pca', with sub-class
'dudi'. See |
bet1 |
An object of class 'bga', with sub-class
'dudi'. See |
bet2 |
An object of class 'bga', with sub-class
'dudi'. See |
This is very computational intensive. The authors of ade4 are currently re-writing the code for coinertia analysis, so that it should substantially improve the computational requirements (May 2004).
Aedin Culhane
Culhane AC, et al., 2003 Cross platform comparison and visualisation of gene expression data using co-inertia analysis. BMC Bioinformatics. 4:59
1 2 |
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