Description Usage Arguments Value References Examples
Empirical power calculation using Royston test statistic.
1 | power.mswR(a, n, p, B = 1000, FUN, ...)
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a |
significance level (α). |
n |
number of rows (observations). |
p |
number of columns (variables), n>p. |
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 |
Returns a numeric value of the estimated empirical power (value between 0 and 1).
Royston, J. P. (1982). An extension of Shapiro and Wilk's W test for normality to large samples. Journal of the Royal Statistical Society: Series C (Applied Statistics), 31(2), 115-124.
1 2 3 4 5 6 | 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.mswR(a = 0.05, n = 50, p = 2, B = 100, FUN=IMMV, D1=runif)
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