The geometric distribution with parameter p is a good model for these data. i) What is the maximum likelihood estimator of p for a geometric model? i) What is the maximum likelihood estimate of p for the data in Table 3? rn fnly
The geometric distribution with parameter p is a good model for these data. i) What is the maximum likelihood estimator of p for a geometric model? i) What is the maximum likelihood estimate of p for the data in Table 3? rn fnly
MATLAB: An Introduction with Applications
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Author:Amos Gilat
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1,c

Transcribed Image Text:(c) Studies of the size and range of wild animal populations often involve
tagging observed individual animals and recording how many times each
is caught in a trap (from which it is then released back into the wild).
The dataset presented in Table 3 consists of the numbers of times each
of n = 334 wood mice were caught in a particular trap (over a two-year
time period).
a ase prodde
Table 3 Numbers of trappings of wood mice
Times trapped
Frequency
4
6.
8.
9.
71
59
41
39
20
26
19
12
9.
Times trapped 10
Frequency
11
12
13
14
15
16
17
18
4
6.
1
3
3
3
The geometric distribution with parameter p is a good model for these
data.
(i) What is the maximum likelihood estimator of p for a geometric
model?
ii) What is the maximum likelihood estimate of p for the data in
Table 3? n fnly
e interval thai you ound
speriants
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