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pchc (version 1.2)

Estimation of the percentage of null p-values: Estimation of the percentage of null p-values

Description

Estimation of the percentage of null p-values.

Usage

pi0est(p, lambda = seq(0.05, 0.95, by = 0.01), dof = 3)

Value

The estimated proportion of non significant (null) p-values. In the paper Storey and Tibshirani mention that the estimate of pi0 is with lambda=1, but in their R code they use the highest value of lambda and thus we do the same here.

Arguments

p

A vector of p-values.

lambda

A vector of values of the tuning parameter lambda.

dof

Number of degrees of freedom to use when estimating pi_0 with smoothing splines.

Author

Michail Tsagris.

R implementation and documentation: Michail Tsagris mtsagris@uoc.gr.

Details

The estimated proporiton of null p-values is estimated the algorithm by Storey and Tibshirani (2003).

References

Storey J.D. and Tibshirani R. (2003). Statistical significance for genome-wide experiments. Proceedings of the National Academy of Sciences, 100: 9440-9445.

See Also

conf.edge.lower, bn.skel.utils, mmhc.skel

Examples

Run this code
A <- pchc::rbn2(1000, p = 20, nei = 3)
x <- A$x
mod <- pchc::mmhc.skel(x, alpha = 0.05 )
pval <- exp(mod$pvalue)
pval <- lower.tri(pval)
pchc::pi0est(pval)

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