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EstDimIC

Dimension estimation by AIC and BIC

Description

Method for estimating latent dimension by AIC and BIC.

Usage

EstDimIC(Rmat,Krange=0:25)

Arguments

Rmat

Residual matrix for which to estimate latent dimension.
Krange

Vector of integers representing candidate dimensions to consider

Details

Method for estimating latent dimension by AIC and BIC. Inferior to the RMT method in the isva package, but it appears here because it's mentioned in our paper.

Value

A list containing AIC and BIC for candidate dimensions, as well as the best dimension for each.

Author(s)

E. Andres Houseman

References

HOUSEMAN, Eugene Andres, MOLITOR, John, et MARSIT, Carmen J. Reference-free cell mixture adjustments in analysis of DNA methylation data. Bioinformatics, 2014, vol. 30, no 10, p. 1431-1439.

See Also

Examples

data(RefFreeEWAS)

## Not run: 
  tmpDesign <- cbind(1, rfEwasExampleCovariate)
  tmpBstar <- rfEwasExampleBetaValues 

  EstDimIC(rfEwasExampleBetaValues-tmpBstar 

## End(Not run)
RefFreeEWAS

EWAS using Reference-Free DNA Methylation Mixture Deconvolution

v2.2
GPL (>= 2)
Authors
E. Andres Houseman, Sc.D.
Initial release
2018-12-14

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