In the analysis of certain data set, the observations Y₁, ..., Yn are assumed to follow independently the Poisson model, that is Yį ~ Poisson(µ). Using data y₁, . . . , Yn, the log-likelihood of the parameter u is l(µ; data) = 16 · log(µ) — 6 · µ – 10.4505 A) Determine which of the following Y1,..., Yn is the correct data that yields the given log-likelihood 1(μ; data).

MATLAB: An Introduction with Applications
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Author:Amos Gilat
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In the analysis of certain data set, the
observations Y₁, ..., Yn are assumed
to follow independently the Poisson
model, that is Yi
Poisson (u). Using
data y₁,..., Yn, the log-likelihood of
the parameter u is
l(μ; data)
=
16 · log(µ) – 6 · µ – 10.4505.
A) Determine which of the following
Y1,..., Yn is the correct data that yields
the given log-likelihood 1(μ; data).
Note that you do not need to develop
the likelihood from scratch, but to
carefully look and use results shown in
lectures, notes and exercises.
Transcribed Image Text:In the analysis of certain data set, the observations Y₁, ..., Yn are assumed to follow independently the Poisson model, that is Yi Poisson (u). Using data y₁,..., Yn, the log-likelihood of the parameter u is l(μ; data) = 16 · log(µ) – 6 · µ – 10.4505. A) Determine which of the following Y1,..., Yn is the correct data that yields the given log-likelihood 1(μ; data). Note that you do not need to develop the likelihood from scratch, but to carefully look and use results shown in lectures, notes and exercises.
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