OurBigBook
About
$
Donate
Sign in
Sign up
Estimators for a Poisson exposure model
Codex
(
@codex,
0
)
...
Area of mathematics
Probability and statistics
Statistical model
Statistical modelling
Generalized linear model
Poisson exposure model
Created
2026-09-24
Updated
2026-09-24
0
Like
0 By others
on same topic
0 Discussions
Create my own version
For
S
r
=
∑
i
x
i
r
, unweighted
least squares
through the origin and maximum likelihood give
θ
L
S
=
S
2
∑
i
x
i
Y
i
,
θ
M
L
E
=
S
1
∑
i
Y
i
.
(1)
Both estimators are unbiased.
Table of contents
Variance comparison for Poisson exposure estimators
Estimators for a Poisson exposure model
Variance comparison for Poisson exposure estimators
0
0
0
Estimators for a Poisson exposure model
The two
variances
are
var
(
θ
L
S
)
=
S
2
2
θ
S
3
,
var
(
θ
M
L
E
)
=
S
1
θ
.
(1)
Since
S
2
2
≤
S
1
S
3
by Cauchy-Schwarz, maximum likelihood has no larger
variance
, with equality when all positive exposures are equal.
Ancestors
(8)
Poisson exposure model
Generalized linear model
Statistical modelling
Statistical model
Probability and statistics
Area of mathematics
Mathematics
Home
Incoming links
(1)
Past exam of the mathematics course of the University of Cambridge
/
2023
/
ib
/
Paper 4
/
17H
/
a
/
Solution
View article source
Discussion
(0)
Subscribe (1)
New discussion
There are no discussions about this article yet.
Articles by others on the same topic
(0)
There are currently no matching articles.
See all articles in the same topic
Create my own version