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each consisting of eight measurements:
clear
data1 = [5 5 8 9 13 13 13 15];
data2 = [3 3 4 5 5 8 10 16];
We concatenate the two samples horizontally and sort the measurements in
ascending order by typing
data = horzcat(data1,data2);
data = sort(data)
which yields the output
data =
Columns 1 through 8
3 3 4 5 5 5 5 8
Columns 9 through 16
8 9 10 13 13 13 15 16
autowrapping those lines that are longer than the width of the Command
Window. We then determine the number of measurements n1 and n2 in
each sample, which is eight for both of the samples in our example. h en we
create a linearly-spaced vector L ranging from 1 to length(data) .
n1 = length(data1);
n2 = length(data2);
L = 1 : length(data)
which yields
L =
Columns 1 through 8
1 2 3 4 5 6 7 8
Columns 9 through 16
9 10 11 12 13 14 15 16
We next i nd the unique values C in the data. h e location vectors ia and ic
help to i nd C = data(ia) and to reconstruct data from data = C(ic) .
We then search for tied values in data . At er we have initialized the
variables by setting them all to zero, the tied values in ic are located using
find and are then stored in dties , with the number of occurrences recorded
in nties . Having located the tied values their ranks are averaged and stored
in icf . We type
nties = 0;
dties = 0;
kties = 0;
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