
Empirical power calculation using VAGE test statistic.
power.mswV(a, n, p, B = 1000, FUN, ...)
significance level (
number of rows (observations).
number of columns (variables),
number of Monte Carlo simulations, default is 1000 (can increase B to increase the precision).
self-defined function for generate multivariate distribution. See example.
optional arguments passed to FUN
.
Returns a numeric value of the estimated empirical power (value between 0 and 1).
Villasenor Alva, J. A., & Estrada, E. G. (2009). A generalization of Shapiro<U+2013>Wilk's test for multivariate normality. Communications in Statistics<U+2014>Theory and Methods, 38(11), 1870-1883.
# NOT RUN {
set.seed(12345)
## Power calculation against bivariate (p=2) independent Beta(1, 1) distribution ##
## at sample size n=50 at one-sided alpha = 0.05 ##
power.mswV(a = 0.05, n = 50, p = 2, B = 100, FUN=IMMV, D1=runif)
# }
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