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Mike <mcross@exemail.com.au>:
I agree with all Nick's points, but it is true that if you have chosen
the kernel width correctly, gaps in the data have estimated density
zero and this fact makes it easy to identify boundaries between groups
of data. The choice of a different kernel width will produce
different group boundaries, of course.
clear
input sampling_event size
1 94.74
2 94.89
3 94.95
4 94.97
5 95
6 95.05
7 95.08
8 96.11
9 96.22
10 96.24
11 96.27
12 96.27
13 96.27
14 96.32
15 96.34
16 97.19
17 97.26
18 97.26
19 97.32
20 97.34
21 97.39
22 98.41
23 100.62
24 100.69
25 100.69
26 100.76
27 100.76
28 100.76
29 100.84
30 100.91
end
twoway__histogram_gen size, width(.1) gen(h z)
kdensity size, bw(.1) g(x f) nogr
g trough=sum(f==0&f[_n-1]!=0)
replace trough=0 if f>0
su trough, mean
loc m
forv i=1/`r(max)' {
qui su x if trough==`i', d
loc m `m' `r(p50)'
}
tw bar h z, barw(.1)||line f x, xli(`m')
di "`m'"