power.usw: Power Calculation using the Univariate Shapiro-Wilk Test...

In mvnormalTest: Powerful Tests for Multivariate Normality

Description

Empirical power calculation using univariate Shapiro-Wilk test statistic.

Usage

power.usw(a, n, p = 1, B = 1000, FUN, ...)

Arguments

a	significance level (α).
n	number of rows (observations).
p	p=1 for univariate.
B	number of Monte Carlo simulations, default is 1000 (can increase B to increase the precision).
FUN	self-defined function for generate multivariate distribution. See example.
...	optional arguments passed to FUN.

Value

Returns a numeric value of the estimated empirical power (value between 0 and 1).

References

Shapiro, S. S., & Wilk, M. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52(3/4), 591-611.

Examples

set.seed(12345)

## Power calculation against univariate (p=1) independent Beta(1, 1) distribution ##
## at sample size n=50 at one-sided alpha = 0.05 ##

power.usw(a = 0.05, n = 50, p = 1,  B = 100, FUN=IMMV, D1=runif)

mvnormalTest documentation built on April 28, 2020, 5:06 p.m.