pareto2.htest(x, y, s, alternative=c("two.sided", "less", "greater"),
significance=0.05, wyg, verbose=TRUE, drho=0.005, K, improve=TRUE)
NULL
. See Value for details.TRUE
then the computation progress will be printed out.K
iff K
is not given.NULL
.TRUE
then the greedy heuristic algorithm for improving the acceptation region will be run.power.htest
with the following components is passed as a result:
statistic
the value of the test statistic.
result
either FALSE (accept null hypothesis) or TRUE (reject).
alternative
a character string describing the alternative hypothesis.
method
a character string indicating what type of test was performed.
data.name
a character string giving the name(s) of the data.
wyg
a numeric vector giving the h-dependent acceptation region used.
size
size of the test corresponding to wyg
.
qual
quality of the test corresponding to wyg
, the closer to significance
, the better.
}
Currently no method for determining the p-value of this test is implemented.alternative
.
It bases on test statistic
T=H(Y)-H(X)
where $H$ denotes Hirsch's $h$-index (see index.h
).Note that for $k_x < k_y$, then $X$ dominates $Y$ stochastically.
dpareto2
, pareto2.goftest
, pareto2.ftest
, pareto2.htest.approx
, index.h