pca

Description

transforms a data set, and returns coordinates in the principal basis.

Usage

1
pca(dat, ncomp = NULL)

Arguments

dat

matrix of row-elements.

ncomp

number of retained variables in the output result. If NULL, all transformed variables are returned.

Value

matrix of transformed row-elements.

Author(s)

Pierrick Bruneau

References

Tipping, M. E. and Bishop, C. M. (1999) _Probabilistic principal component analysis_ ,Journal of the Royal Statistical Society - B Series, Volume 61, Number 3, Pages 611-622.

Bruneau, P., Gelgon, M. and Picarougne, F. (2010) _Aggregation of probabilistic PCA mixtures with a variational-Bayes technique over parameters_, ICPR'10.

Bruneau, P., Gelgon, M. and Picarougne, F. (2011) _Component-level aggregation of probabilistic PCA mixtures using variational-Bayes_, Tech Report, http://hal.archives-ouvertes.fr/docs/00/56/72/99/PDF/techrep.pdf.

See Also

mppca

Examples

1
temp <- pca(irisdata, 3)

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