mixfdr: Computes false discovery rates and effect sizes using normal mixtures , This package fits normal mixture models to data and uses them to compute effect size estimates and local and tail area false discovery rates. To make this precise, suppose you have many normally distributed z’s, and each z[i] has mean delta[i]. This package will estimate delta[i] based on the z’s (effect sizes), P(delta[i]=0|z[i]) (local false discovery rates) and P(delta[i]=0||z[i]|>z) (tail area false discovery rates). (Source: http://cran.r-project.org/web/packages)
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References in zbMATH (referenced in 4 articles )
Showing results 1 to 4 of 4.
- Heller, Ruth; Yekutieli, Daniel: Replicability analysis for genome-wide association studies (2014)
- Phillips, Daisy; Ghosh, Debashis: Testing the disjunction hypothesis using Voronoi diagrams with applications to genetics (2014)
- Muralidharan, Omkar: High dimensional exponential family estimation via empirical Bayes (2012)
- Muralidharan, Omkar: An empirical Bayes mixture method for effect size and false discovery rate estimation (2010)