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Monte Carlo-based EDMA-II testing procedure
The difference between EDMA-I and EDMA-II is described in detail in
Part 1 of this chapter. We do not repeat the discussion here.
STEP 1: Calculate the shape difference matrix using the esti-
mated mean forms for the two populations. Calculate the
extreme value in the shape difference matrix, either negative
or positive.
STEP 2: Assuming that the first population is the base sam-
ple, generate a new set of samples X 1 * , X 2 * ,…, X n *
from
ˆ
, ˆ
ˆ
, ˆ
and Y 1 * , Y 2 * ,…, Y m * from .
STEP 3: Calculate the shape difference matrix based on these
samples and calculate the most extreme value, negative or
positive and call it T * .
STEP 4: Repeat Steps 2 and 3 B times to obtain T 1 * , T 2 * ,…, T B * .
STEP 5: Arrange T 1 * , T 2 * ,…, T B * in an increasing order. Assume
that the size of the test is 0.10, then calculate the 5-th per-
centile and the 95-th percentile values of these T * 's. If zero
lies in between these values, then accept the null hypothesis
of equality of shapes, otherwise reject it.
NM
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,)
I
NM
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I
1
K
,
1
1
K
,
1
We want to reemphasize the fact that if the distribution of the test
statistic is bimodal, one should not conduct the above test. In general,
we prefer the confidence intervals for the shape or form difference
matrices over simplistic null hypothesis testing.
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