pi0 (version 1.4-1)

nparncpp : Estimation of the density of absolute noncentrality parameters

Description

Estimation of the density of absolute noncentrality parameters, using linear B-spline model.

Usage

nparncpp(p,
    breaks=min(2000,round(length(p)/5)),
    test=c("t","z"),
    df,
    alternative=c("two.sided", "less", "greater"),
    compromise.n=1,
    lambdas=#if(penalty_type==1)10^seq(-2,6,length=6) else 
            10^seq(-4,6,length=11),
    deltamax='auto',
    nknots,
    ndelta=500,
    solver=c("lsei","LowRankQP","solve.QP","ipop"),
    weights=1,
    keep.cdf=NULL,
    LowRankQP.method=c('LU','CHOL'),
    lsei.method=c('chol','svd','eigen'),
    debugging=FALSE,
    ...)

Arguments

p

p-value vector

breaks

break points to bin the p-values

test

either t-test or z-test

df

degrees of freedom for the test

alternative

Same as in t.test

compromise.n

Number of components in the compromised estimate

lambdas

Candidate tuning parameters

deltamax

Assumed maximum noncentrality parameters

nknots

Number of knots

ndelta

Number of points to evaluate the noncentrality parameters

solver

Quadratic programming solver function

weights

Bin weights

keep.cdf

Either NULL or an environment. If non-null, the computed computed conditional CDF will be saved keep.cdf. See cond.cdf.

LowRankQP.method

Method for LowRankQP

lsei.method

Method for lsei

debugging

Logical: print excessive messages

…

Additional argumenets to solver

Value

An object of class c('nparncpp','ncpest').

References

Ruppert, Nettleton, Hwang. (2007) Exploring the Information in \(p\)-values for the Analysis and Planning of Multiple-test Experiments. Biometrics. 63. 483-495.

See Also

nparncpt, sparncpt, parncpt, dncp