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=TRUE,
LowRankQP.method=c('LU','CHOL'),
lsei.method=c('chol','svd','eigen'),
debugging=FALSE,
...)
Arguments
breaks
break points to bin the p-values
test
either t
-test or z
-test
df
degrees of freedom for the test
compromise.n
Number of components in the compromised estimate
lambdas
Candidate tuning parameters
deltamax
Assumed maximum noncentrality parameters
ndelta
Number of points to evaluate the noncentrality parameters
solver
Quadratic programming solver function
keep.cdf
Logical: whether computed conditional CDF is saved in global enviroment. See cond.cdf
. debugging
Logical: print excessive messages
...
Additional argumenets to solver