Monte Carlo comparison of four normality tests using different entropy estimates
Communications in Statistics-Simulation and computation, 2001•Taylor & Francis
The paper studies four entropy tests of normality of real valued observations using four
statistics based on different entropy estimates from n iid observations. For the test size α=
0.05 and sample sizes 5≤ n≤ 50, it presents critical values of the test statistics. It also
compares the power and robustness of these four tests using Monte Carlo computations for
sample sizes n= 10 and n= 20. Preferences between the tests based on these computations
can be extrapolated for small sample sizes.
statistics based on different entropy estimates from n iid observations. For the test size α=
0.05 and sample sizes 5≤ n≤ 50, it presents critical values of the test statistics. It also
compares the power and robustness of these four tests using Monte Carlo computations for
sample sizes n= 10 and n= 20. Preferences between the tests based on these computations
can be extrapolated for small sample sizes.
The paper studies four entropy tests of normality of real valued observations using four statistics based on different entropy estimates from n i.i.d. observations. For the test size α = 0.05 and sample sizes 5 ≤ n ≤ 50, it presents critical values of the test statistics. It also compares the power and robustness of these four tests using Monte Carlo computations for sample sizes n = 10 and n = 20. Preferences between the tests based on these computations can be extrapolated for small sample sizes.
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