HoggAdapt


    response variable (numeric vector)
  


  Implements the recommendations of Hogg et al. (1975) for data-driven selection of rank-based permutation test statistics. It is designed to select a powerful test statistic given the tailweight and skew of the distribution of <code>y</code>. Best used for continuous distributions that differ in location only (i.e., under a constant treatment effect assumption).


 ~kwd1 

 ~kwd2 

An implementation of nonparametric combination of hypothesis tests.
This package performs nonparametric combination (Pesarin and Salmaso 2010),
a permutation-based procedure for jointly testing multiple hypotheses. The
tests are conducted under the global "sharp" null hypothesis of no effects,
and the component tests are combined on the metric of their p-values. A
key feature of nonparametric combination is that it accounts for the
dependence among tests under the null hypothesis. In addition to the
"NPC" function, which performs nonparametric combination itself, the
package also contains a number of helper functions, many of which calculate
a test statistic given an input of data.

HoggAdapt: Adaptive Choice of Rank-Based Test Statistic

Description

Usage

Arguments

Value

References

See Also