mirf (1.0)

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MULTIPLE IMPUTATION AND RANDOM FORESTS FOR UNOBSERVABLE PHASE, HIGH-DIMENSIONAL DATA.

http://www-unix.oit.umass.edu/~foulkes/
http://cran.r-project.org/web/packages/mirf

This package applies a combination of missing haplotype imputation via the EM algorithm of Excoffier and Slatkin(1995) and modelling trait-haplotype associations via the Random Forest algorithm. The EM algorithm is implemented by the function haplo.em (of the haplo.stats package) and the Random Forest algorithm is implemented by the randomForest function (of the randomForest package). This method is described in the published manuscript: B.A.S. Nonyane and A.S. Foulkes (2007) Multiple imputation and random forests (MIRF) for unobservable high-dimensional data. The International Journal of Biostatistics 3(1): Article 12.

Maintainer: Yimin Wu
Author(s): Yimin Wu, B. Aletta S. Nonyane and Andrea S. Foulkes

License: BSD

Uses: haplo.stats, randomForest

Released over 10 years ago.


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