Finding an expected value [duplicate]
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Compute the mean of $(1 + X)^{-1}$ where $X$ is Poisson$(lambda)$
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Below is a problem that I did from Chapter 4 of the book "Intoduction to Probability Theory". The book was written by Hoel, Port and Stone. The answer I got is wrong. I would like to know what I
did wrong.
Thanks,
Bob
Problem:
Let $X$ be a Poisson with parameter $lambda$. Compute the mean of
$(1+X)^{-1}$.
Answer:
The density function for the Poisson distribution is:
$$f(x) = frac{lambda^x e ^ {-x}}{x!}$$
Let $u$ be the mean that we seek.
begin{eqnarray*}
u &=& sum_{x = 0}^{infty} frac{lambda^x e ^ {-x}}{x!((1+x))} =
sum_{x = 0}^{infty} frac{lambda^x e ^ {-x}}{(x+1)!} \
u &=& sum_{x = 1}^{infty} frac{lambda^x e ^ {-(x-1)}}{(x)!} \
u &=& sum_{x = 1}^{infty} frac{lambda^x e ^ {-x + 1}}{(x)!} \
u &=& e sum_{x = 1}^{infty} frac{lambda^x e ^ {-x}}{(x)!} \
end{eqnarray*}
Observe that when $lambda$ is very large that $u$ is very large. Therefore, I conclude
that I am already wrong. The books answer is:
$$ lambda^{-1}(1-e^{-lambda}) $$
probability
marked as duplicate by StubbornAtom, Lord Shark the Unknown, Trevor Gunn, Gibbs, Shailesh Nov 17 at 0:05
This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.
add a comment |
up vote
2
down vote
favorite
This question already has an answer here:
Compute the mean of $(1 + X)^{-1}$ where $X$ is Poisson$(lambda)$
3 answers
Below is a problem that I did from Chapter 4 of the book "Intoduction to Probability Theory". The book was written by Hoel, Port and Stone. The answer I got is wrong. I would like to know what I
did wrong.
Thanks,
Bob
Problem:
Let $X$ be a Poisson with parameter $lambda$. Compute the mean of
$(1+X)^{-1}$.
Answer:
The density function for the Poisson distribution is:
$$f(x) = frac{lambda^x e ^ {-x}}{x!}$$
Let $u$ be the mean that we seek.
begin{eqnarray*}
u &=& sum_{x = 0}^{infty} frac{lambda^x e ^ {-x}}{x!((1+x))} =
sum_{x = 0}^{infty} frac{lambda^x e ^ {-x}}{(x+1)!} \
u &=& sum_{x = 1}^{infty} frac{lambda^x e ^ {-(x-1)}}{(x)!} \
u &=& sum_{x = 1}^{infty} frac{lambda^x e ^ {-x + 1}}{(x)!} \
u &=& e sum_{x = 1}^{infty} frac{lambda^x e ^ {-x}}{(x)!} \
end{eqnarray*}
Observe that when $lambda$ is very large that $u$ is very large. Therefore, I conclude
that I am already wrong. The books answer is:
$$ lambda^{-1}(1-e^{-lambda}) $$
probability
marked as duplicate by StubbornAtom, Lord Shark the Unknown, Trevor Gunn, Gibbs, Shailesh Nov 17 at 0:05
This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.
1
There are many books of this title. Who wrote it?
– Sean Roberson
Nov 15 at 23:40
add a comment |
up vote
2
down vote
favorite
up vote
2
down vote
favorite
This question already has an answer here:
Compute the mean of $(1 + X)^{-1}$ where $X$ is Poisson$(lambda)$
3 answers
Below is a problem that I did from Chapter 4 of the book "Intoduction to Probability Theory". The book was written by Hoel, Port and Stone. The answer I got is wrong. I would like to know what I
did wrong.
Thanks,
Bob
Problem:
Let $X$ be a Poisson with parameter $lambda$. Compute the mean of
$(1+X)^{-1}$.
Answer:
The density function for the Poisson distribution is:
$$f(x) = frac{lambda^x e ^ {-x}}{x!}$$
Let $u$ be the mean that we seek.
begin{eqnarray*}
u &=& sum_{x = 0}^{infty} frac{lambda^x e ^ {-x}}{x!((1+x))} =
sum_{x = 0}^{infty} frac{lambda^x e ^ {-x}}{(x+1)!} \
u &=& sum_{x = 1}^{infty} frac{lambda^x e ^ {-(x-1)}}{(x)!} \
u &=& sum_{x = 1}^{infty} frac{lambda^x e ^ {-x + 1}}{(x)!} \
u &=& e sum_{x = 1}^{infty} frac{lambda^x e ^ {-x}}{(x)!} \
end{eqnarray*}
Observe that when $lambda$ is very large that $u$ is very large. Therefore, I conclude
that I am already wrong. The books answer is:
$$ lambda^{-1}(1-e^{-lambda}) $$
probability
This question already has an answer here:
Compute the mean of $(1 + X)^{-1}$ where $X$ is Poisson$(lambda)$
3 answers
Below is a problem that I did from Chapter 4 of the book "Intoduction to Probability Theory". The book was written by Hoel, Port and Stone. The answer I got is wrong. I would like to know what I
did wrong.
Thanks,
Bob
Problem:
Let $X$ be a Poisson with parameter $lambda$. Compute the mean of
$(1+X)^{-1}$.
Answer:
The density function for the Poisson distribution is:
$$f(x) = frac{lambda^x e ^ {-x}}{x!}$$
Let $u$ be the mean that we seek.
begin{eqnarray*}
u &=& sum_{x = 0}^{infty} frac{lambda^x e ^ {-x}}{x!((1+x))} =
sum_{x = 0}^{infty} frac{lambda^x e ^ {-x}}{(x+1)!} \
u &=& sum_{x = 1}^{infty} frac{lambda^x e ^ {-(x-1)}}{(x)!} \
u &=& sum_{x = 1}^{infty} frac{lambda^x e ^ {-x + 1}}{(x)!} \
u &=& e sum_{x = 1}^{infty} frac{lambda^x e ^ {-x}}{(x)!} \
end{eqnarray*}
Observe that when $lambda$ is very large that $u$ is very large. Therefore, I conclude
that I am already wrong. The books answer is:
$$ lambda^{-1}(1-e^{-lambda}) $$
This question already has an answer here:
Compute the mean of $(1 + X)^{-1}$ where $X$ is Poisson$(lambda)$
3 answers
probability
probability
edited Nov 15 at 23:58
asked Nov 15 at 23:31
Bob
840514
840514
marked as duplicate by StubbornAtom, Lord Shark the Unknown, Trevor Gunn, Gibbs, Shailesh Nov 17 at 0:05
This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.
marked as duplicate by StubbornAtom, Lord Shark the Unknown, Trevor Gunn, Gibbs, Shailesh Nov 17 at 0:05
This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.
1
There are many books of this title. Who wrote it?
– Sean Roberson
Nov 15 at 23:40
add a comment |
1
There are many books of this title. Who wrote it?
– Sean Roberson
Nov 15 at 23:40
1
1
There are many books of this title. Who wrote it?
– Sean Roberson
Nov 15 at 23:40
There are many books of this title. Who wrote it?
– Sean Roberson
Nov 15 at 23:40
add a comment |
3 Answers
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The Poisson distribution is
$$f(x) = frac{lambda^x e ^ {-{color{red}{lambda}}}}{x!}, x in mathbb{N}. $$
Therefore, the expected value $u$ of $(1+X)^{-1}$ is:
$$u = sum_{x = 0}^{infty} frac{lambda^x e ^ {-lambda}}{x!(1+x)} = e ^ {-lambda}sum_{x = 0}^{infty} frac{lambda^x}{(1+x)!}.$$
Now, do a substitution $t = x+1$:
$$u = e ^ {-lambda}sum_{t = 1}^{infty} frac{lambda^{t-1} }{t!} = frac{e^{-lambda}}{lambda}sum_{t = 1}^{infty} frac{lambda^{t}}{t!} = frac{e^{-lambda}}{lambda}left(sum_{t = 0}^{infty} frac{lambda^{t}}{t!} - 1right).$$
It is well-known that:
$$sum_{t = 0}^{infty} frac{lambda^{t} }{t!} = e^{lambda}.$$
You can check this fact here.
Finally:
$$u = frac{e^{-lambda}}{lambda}(e^{lambda}-1) = frac{1}{lambda}(1-e^{-lambda}) = lambda^{-1}(1-e^{-lambda}).$$
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1
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Your $f(x)$ is not correct. The term $e^{-x}$ should be $e^{-lambda}$.
From your first line to the second, when you offset $x$ by $1$, you should have $lambda^{x-1}$ in the numerator. That would lead you to pull a factor $lambda^{-1}$ out of the sum, fixing that part.
Then the final sum would be $1$ if it went from $0$ to $infty$, so it is $1$ minus the $x=0$ term giving $1-e^{-lambda}$
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begin{eqnarray*}
u &=& sum_{x = 0}^{infty} frac{lambda^x e ^ {-color{red}{lambda}}}{x!((1+x))}\ &=&
sum_{x = 0}^{infty} frac{lambda^x e ^ {-lambda}}{(x+1)!} \
&=& sum_{x = 1}^{infty} frac{lambda^{x-1} e ^ {-lambda}}{x!} \
&=& frac 1lambdasum_{x = 1}^{infty} frac{lambda^x e ^ {-lambda}}{x!}
\ &=& frac 1lambdaleft(sum_{x = 0}^{infty} frac{lambda^x e ^ {-lambda}}{x!}-e^{-lambda}right) \ &vdots&
end{eqnarray*}
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3 Answers
3
active
oldest
votes
3 Answers
3
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
0
down vote
accepted
The Poisson distribution is
$$f(x) = frac{lambda^x e ^ {-{color{red}{lambda}}}}{x!}, x in mathbb{N}. $$
Therefore, the expected value $u$ of $(1+X)^{-1}$ is:
$$u = sum_{x = 0}^{infty} frac{lambda^x e ^ {-lambda}}{x!(1+x)} = e ^ {-lambda}sum_{x = 0}^{infty} frac{lambda^x}{(1+x)!}.$$
Now, do a substitution $t = x+1$:
$$u = e ^ {-lambda}sum_{t = 1}^{infty} frac{lambda^{t-1} }{t!} = frac{e^{-lambda}}{lambda}sum_{t = 1}^{infty} frac{lambda^{t}}{t!} = frac{e^{-lambda}}{lambda}left(sum_{t = 0}^{infty} frac{lambda^{t}}{t!} - 1right).$$
It is well-known that:
$$sum_{t = 0}^{infty} frac{lambda^{t} }{t!} = e^{lambda}.$$
You can check this fact here.
Finally:
$$u = frac{e^{-lambda}}{lambda}(e^{lambda}-1) = frac{1}{lambda}(1-e^{-lambda}) = lambda^{-1}(1-e^{-lambda}).$$
add a comment |
up vote
0
down vote
accepted
The Poisson distribution is
$$f(x) = frac{lambda^x e ^ {-{color{red}{lambda}}}}{x!}, x in mathbb{N}. $$
Therefore, the expected value $u$ of $(1+X)^{-1}$ is:
$$u = sum_{x = 0}^{infty} frac{lambda^x e ^ {-lambda}}{x!(1+x)} = e ^ {-lambda}sum_{x = 0}^{infty} frac{lambda^x}{(1+x)!}.$$
Now, do a substitution $t = x+1$:
$$u = e ^ {-lambda}sum_{t = 1}^{infty} frac{lambda^{t-1} }{t!} = frac{e^{-lambda}}{lambda}sum_{t = 1}^{infty} frac{lambda^{t}}{t!} = frac{e^{-lambda}}{lambda}left(sum_{t = 0}^{infty} frac{lambda^{t}}{t!} - 1right).$$
It is well-known that:
$$sum_{t = 0}^{infty} frac{lambda^{t} }{t!} = e^{lambda}.$$
You can check this fact here.
Finally:
$$u = frac{e^{-lambda}}{lambda}(e^{lambda}-1) = frac{1}{lambda}(1-e^{-lambda}) = lambda^{-1}(1-e^{-lambda}).$$
add a comment |
up vote
0
down vote
accepted
up vote
0
down vote
accepted
The Poisson distribution is
$$f(x) = frac{lambda^x e ^ {-{color{red}{lambda}}}}{x!}, x in mathbb{N}. $$
Therefore, the expected value $u$ of $(1+X)^{-1}$ is:
$$u = sum_{x = 0}^{infty} frac{lambda^x e ^ {-lambda}}{x!(1+x)} = e ^ {-lambda}sum_{x = 0}^{infty} frac{lambda^x}{(1+x)!}.$$
Now, do a substitution $t = x+1$:
$$u = e ^ {-lambda}sum_{t = 1}^{infty} frac{lambda^{t-1} }{t!} = frac{e^{-lambda}}{lambda}sum_{t = 1}^{infty} frac{lambda^{t}}{t!} = frac{e^{-lambda}}{lambda}left(sum_{t = 0}^{infty} frac{lambda^{t}}{t!} - 1right).$$
It is well-known that:
$$sum_{t = 0}^{infty} frac{lambda^{t} }{t!} = e^{lambda}.$$
You can check this fact here.
Finally:
$$u = frac{e^{-lambda}}{lambda}(e^{lambda}-1) = frac{1}{lambda}(1-e^{-lambda}) = lambda^{-1}(1-e^{-lambda}).$$
The Poisson distribution is
$$f(x) = frac{lambda^x e ^ {-{color{red}{lambda}}}}{x!}, x in mathbb{N}. $$
Therefore, the expected value $u$ of $(1+X)^{-1}$ is:
$$u = sum_{x = 0}^{infty} frac{lambda^x e ^ {-lambda}}{x!(1+x)} = e ^ {-lambda}sum_{x = 0}^{infty} frac{lambda^x}{(1+x)!}.$$
Now, do a substitution $t = x+1$:
$$u = e ^ {-lambda}sum_{t = 1}^{infty} frac{lambda^{t-1} }{t!} = frac{e^{-lambda}}{lambda}sum_{t = 1}^{infty} frac{lambda^{t}}{t!} = frac{e^{-lambda}}{lambda}left(sum_{t = 0}^{infty} frac{lambda^{t}}{t!} - 1right).$$
It is well-known that:
$$sum_{t = 0}^{infty} frac{lambda^{t} }{t!} = e^{lambda}.$$
You can check this fact here.
Finally:
$$u = frac{e^{-lambda}}{lambda}(e^{lambda}-1) = frac{1}{lambda}(1-e^{-lambda}) = lambda^{-1}(1-e^{-lambda}).$$
answered Nov 15 at 23:45
the_candyman
8,54921944
8,54921944
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Your $f(x)$ is not correct. The term $e^{-x}$ should be $e^{-lambda}$.
From your first line to the second, when you offset $x$ by $1$, you should have $lambda^{x-1}$ in the numerator. That would lead you to pull a factor $lambda^{-1}$ out of the sum, fixing that part.
Then the final sum would be $1$ if it went from $0$ to $infty$, so it is $1$ minus the $x=0$ term giving $1-e^{-lambda}$
add a comment |
up vote
1
down vote
Your $f(x)$ is not correct. The term $e^{-x}$ should be $e^{-lambda}$.
From your first line to the second, when you offset $x$ by $1$, you should have $lambda^{x-1}$ in the numerator. That would lead you to pull a factor $lambda^{-1}$ out of the sum, fixing that part.
Then the final sum would be $1$ if it went from $0$ to $infty$, so it is $1$ minus the $x=0$ term giving $1-e^{-lambda}$
add a comment |
up vote
1
down vote
up vote
1
down vote
Your $f(x)$ is not correct. The term $e^{-x}$ should be $e^{-lambda}$.
From your first line to the second, when you offset $x$ by $1$, you should have $lambda^{x-1}$ in the numerator. That would lead you to pull a factor $lambda^{-1}$ out of the sum, fixing that part.
Then the final sum would be $1$ if it went from $0$ to $infty$, so it is $1$ minus the $x=0$ term giving $1-e^{-lambda}$
Your $f(x)$ is not correct. The term $e^{-x}$ should be $e^{-lambda}$.
From your first line to the second, when you offset $x$ by $1$, you should have $lambda^{x-1}$ in the numerator. That would lead you to pull a factor $lambda^{-1}$ out of the sum, fixing that part.
Then the final sum would be $1$ if it went from $0$ to $infty$, so it is $1$ minus the $x=0$ term giving $1-e^{-lambda}$
answered Nov 15 at 23:41
Ross Millikan
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287k23195364
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begin{eqnarray*}
u &=& sum_{x = 0}^{infty} frac{lambda^x e ^ {-color{red}{lambda}}}{x!((1+x))}\ &=&
sum_{x = 0}^{infty} frac{lambda^x e ^ {-lambda}}{(x+1)!} \
&=& sum_{x = 1}^{infty} frac{lambda^{x-1} e ^ {-lambda}}{x!} \
&=& frac 1lambdasum_{x = 1}^{infty} frac{lambda^x e ^ {-lambda}}{x!}
\ &=& frac 1lambdaleft(sum_{x = 0}^{infty} frac{lambda^x e ^ {-lambda}}{x!}-e^{-lambda}right) \ &vdots&
end{eqnarray*}
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begin{eqnarray*}
u &=& sum_{x = 0}^{infty} frac{lambda^x e ^ {-color{red}{lambda}}}{x!((1+x))}\ &=&
sum_{x = 0}^{infty} frac{lambda^x e ^ {-lambda}}{(x+1)!} \
&=& sum_{x = 1}^{infty} frac{lambda^{x-1} e ^ {-lambda}}{x!} \
&=& frac 1lambdasum_{x = 1}^{infty} frac{lambda^x e ^ {-lambda}}{x!}
\ &=& frac 1lambdaleft(sum_{x = 0}^{infty} frac{lambda^x e ^ {-lambda}}{x!}-e^{-lambda}right) \ &vdots&
end{eqnarray*}
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begin{eqnarray*}
u &=& sum_{x = 0}^{infty} frac{lambda^x e ^ {-color{red}{lambda}}}{x!((1+x))}\ &=&
sum_{x = 0}^{infty} frac{lambda^x e ^ {-lambda}}{(x+1)!} \
&=& sum_{x = 1}^{infty} frac{lambda^{x-1} e ^ {-lambda}}{x!} \
&=& frac 1lambdasum_{x = 1}^{infty} frac{lambda^x e ^ {-lambda}}{x!}
\ &=& frac 1lambdaleft(sum_{x = 0}^{infty} frac{lambda^x e ^ {-lambda}}{x!}-e^{-lambda}right) \ &vdots&
end{eqnarray*}
begin{eqnarray*}
u &=& sum_{x = 0}^{infty} frac{lambda^x e ^ {-color{red}{lambda}}}{x!((1+x))}\ &=&
sum_{x = 0}^{infty} frac{lambda^x e ^ {-lambda}}{(x+1)!} \
&=& sum_{x = 1}^{infty} frac{lambda^{x-1} e ^ {-lambda}}{x!} \
&=& frac 1lambdasum_{x = 1}^{infty} frac{lambda^x e ^ {-lambda}}{x!}
\ &=& frac 1lambdaleft(sum_{x = 0}^{infty} frac{lambda^x e ^ {-lambda}}{x!}-e^{-lambda}right) \ &vdots&
end{eqnarray*}
edited Nov 15 at 23:48
answered Nov 15 at 23:42
Graham Kemp
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84k43378
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1
There are many books of this title. Who wrote it?
– Sean Roberson
Nov 15 at 23:40