power.msk {mvnormalTest}

Power Calculation using the Bowman and Shenton Test Statistic

Description

Empirical power calculation using Bowman and Shenton Test Statistic.

Usage

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

Arguments

a

significance level (\alpha).

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 FUN.

Value

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

References

Bowman, K. O., & Shenton, L. R. (1975). Omnibus test contours for departures from normality based on \sqrt b_1 and b_2. Biometrika, 62(2), 243-250.

Examples

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.msk(a = 0.05, n = 50, p = 2,  B = 100, FUN=IMMV, D1=runif)