markerSearchPower-internal {markerSearchPower}R Documentation

Internal functions

Description

Internal markerSearchPower functions.

Usage

CDF.F3l1(x, c, d)
CDF.F4l3(x)
CDF.F34(x)
CDF.T3(x)
covT1l3T2l3Func(b1, b2, b3, p1, p2, sigm)
covT1T1l3Func(b1, b2, b3, p1, p2, sigm)
covT1T2Func(b1, b2, b3, p1, p2, sigm)
covT1T2l3Func(b1, b2, b3, p1, p2, sigm)
covT12T1Func(b1, b2, b3, p1, p2, sigm)
meanF3l1Func(b1, b2, b3, p1, p2, p3, sigm)
meanT1Func(b1, b2, b3, p1, p2, sigm, n)
meanT1l3Func(b1, b2, b3, p1, p2, sigm, n)
meanT12Func(b1, b2, b3, p1, p2, sigm, n)
PDF.F34(x)
power.exhaustive.atleast1(meanT12, meanT1, meanT2, covMT12s, c3l1, 
                          d3l1, c3l2, d3l2, R, p, n, samplePointN)
power.exhaustive.both(meanT12, meanT1, meanT2, covMT12s, c3l1, d3l1, 
                     c3l2, d3l2, R, p, n, samplePointN)
power.forward.atleast1(meanT1, meanT2, meanT1l3, meanT2l3, covMTvector, 
                       R, p, samplePointN, decompMethod)
power.forward.both(meanT12, meanT1, meanT2, covMT12s, c3l1, d3l1, 
                   c3l2, d3l2, R, p, n, samplePointN)
power.marginal(meanT1, meanT2, covMT1T2, R, p, isBoth, samplePointN)
tripleSet(r, p, F34N)
tripleSet2(r, p1, p2, F34N)
varF3l1Func(b1, b2, b3, p1, p2, p3, sigm)
varT1Func(b1, b2, b3, p1, p2, sigm)
varT1l3Func(b1, b2, b3, p1, p2, sigm)
varT12Func(b1, b2, b3, p1, p2, sigm)

Details

These functions are not for use at user level.

Value

CDF.F3l1, CDF.F4l3, CDF.F34, CDF.T3 give discribution functions. PDF.F34 gives density functions. meanF3l1Func, meanT1Func, meanT1l3Func, meanT12Func give means for relevant asymptotic distributions. varF3l1Func, varT1Func, varT1l3Func, varT12Func give variances for relevant asymptotic distributions. covT1l3T2l3Func, covT1T1l3Func, covT1T2Func, covT1T2l3Func, covT12T1Func give covariances for relevant asymptotic distributions. power.xx give calculated power values. tripleSet, tripleSet2 return all possible distributions in three groups for finite samples.

Author(s)

Zheyang Wu

References

Zheyang Wu and Hongyu Zhao (2009) Statistical Power of Model Selection Strategies for Genome-Wide Association Studies. Submitted


[Package markerSearchPower version 1.0 Index]