hmp.stat: Compute the Harmonic Mean _p_-Value

In harmonicmeanp: Harmonic Mean p-Values and Model Averaging by Mean Maximum Likelihood

Compute the Harmonic Mean p-Value

Description

The harmonic mean p-value (HMP) is defined as the inverse of the (possibly weighted) arithmetic mean of the inverse p-values. When the HMP is small (e.g. less than 0.05), it is approximately well-calibrated, meaning that it can be directly interpreted. However, the function p.hmp calculates an asymptotically exact p-value from the HMP and is preferred.

Usage

hmp.stat(p, w = NULL)

Arguments

p	A numeric vector of one or more p-values. Missing values (NAs) will cause a missing value to be returned.
w	An optional numeric vector of weights that can be interpreted as prior model probabilities for each of the alternative hypotheses represented by the individual p-values. The sum of the weights cannot exceed one but may be less than one, which is interpreted as meaning that some p-values have been excluded.

Value

The harmonic mean p-value is returned.

Author(s)

Daniel J. Wilson

References

Daniel J. Wilson (2019) The harmonic mean p-value for combining dependent tests. Proceedings of the National Academy of Sciences USA 116: 1195-1200.

See Also

p.hmp

Examples

# For detailed examples type vignette("harmonicmeanp")
p = rbeta(1000,1/1.5,1)
hmp.stat(p)
p.hmp(p,L=1000)

harmonicmeanp documentation built on May 29, 2024, 1:25 a.m.