Strong law of large numbers for Poisson rvs with different parameter
$begingroup$
Let $X_n$ be independent Poisson random variables with $E[X_i] = mu_i$, and let $Y_n = X_1+...+X_n$. I want to show that if $sum_n mu_n = infty $ then $Y_n/E[Y_n] rightarrow 1$ almost surly.
What I do know is that if $X_1,...$ are independent, and $Eleft[X^4right] < infty$, then $Y_n/n rightarrow E[X]$ a.s.* So What I tried is to center the random variables: let $C_n := X_n-mu_n$. The $C$'s are independent, $E[C_n^4]< infty, E[C_n] = 0$, which means:
$frac{C_1 +...+C_n}{n} rightarrow 0$ a.s., or $frac{sum X_i - sum mu_i}{n} rightarrow 0$ a.s. which, I think, completes the proof.
However I am not sure why the requirement $sum_n mu_n = infty $ is necessary, so I suspect this proof is incorrect. Is it?
Edit: This argument is incorrect since the theorem requires $E[C^4]$ to be uniformly bounded, not just bounded. Any ideas?
- This is the statement of the theorem from "Probability with Martingales"
probability probability-theory probability-distributions poisson-distribution law-of-large-numbers
$endgroup$
|
show 4 more comments
$begingroup$
Let $X_n$ be independent Poisson random variables with $E[X_i] = mu_i$, and let $Y_n = X_1+...+X_n$. I want to show that if $sum_n mu_n = infty $ then $Y_n/E[Y_n] rightarrow 1$ almost surly.
What I do know is that if $X_1,...$ are independent, and $Eleft[X^4right] < infty$, then $Y_n/n rightarrow E[X]$ a.s.* So What I tried is to center the random variables: let $C_n := X_n-mu_n$. The $C$'s are independent, $E[C_n^4]< infty, E[C_n] = 0$, which means:
$frac{C_1 +...+C_n}{n} rightarrow 0$ a.s., or $frac{sum X_i - sum mu_i}{n} rightarrow 0$ a.s. which, I think, completes the proof.
However I am not sure why the requirement $sum_n mu_n = infty $ is necessary, so I suspect this proof is incorrect. Is it?
Edit: This argument is incorrect since the theorem requires $E[C^4]$ to be uniformly bounded, not just bounded. Any ideas?
- This is the statement of the theorem from "Probability with Martingales"
probability probability-theory probability-distributions poisson-distribution law-of-large-numbers
$endgroup$
1
$begingroup$
You cannot apply the result you recall since it requires the increments are identically distributed -- which is not true in your case (except if $mu_n$ does not depend on $mu$).
$endgroup$
– Did
Dec 16 '18 at 13:04
$begingroup$
To see why the $sum_nmu_n=infty$ requirement is needed consider what happens if $mu_1=1$ and $mu_n=0$ for $n>1$.
$endgroup$
– kimchi lover
Dec 16 '18 at 13:07
$begingroup$
@Did - The result I cited does not require i.d. See "Probability with martingales" Chapter 7
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 13:15
$begingroup$
Except you misquoted heavily.
$endgroup$
– Did
Dec 16 '18 at 13:17
$begingroup$
@kimchilover If $mu_n = 0$ it would mean that $X_n = 0$, so I am not sure where is the problem
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 13:17
|
show 4 more comments
$begingroup$
Let $X_n$ be independent Poisson random variables with $E[X_i] = mu_i$, and let $Y_n = X_1+...+X_n$. I want to show that if $sum_n mu_n = infty $ then $Y_n/E[Y_n] rightarrow 1$ almost surly.
What I do know is that if $X_1,...$ are independent, and $Eleft[X^4right] < infty$, then $Y_n/n rightarrow E[X]$ a.s.* So What I tried is to center the random variables: let $C_n := X_n-mu_n$. The $C$'s are independent, $E[C_n^4]< infty, E[C_n] = 0$, which means:
$frac{C_1 +...+C_n}{n} rightarrow 0$ a.s., or $frac{sum X_i - sum mu_i}{n} rightarrow 0$ a.s. which, I think, completes the proof.
However I am not sure why the requirement $sum_n mu_n = infty $ is necessary, so I suspect this proof is incorrect. Is it?
Edit: This argument is incorrect since the theorem requires $E[C^4]$ to be uniformly bounded, not just bounded. Any ideas?
- This is the statement of the theorem from "Probability with Martingales"
probability probability-theory probability-distributions poisson-distribution law-of-large-numbers
$endgroup$
Let $X_n$ be independent Poisson random variables with $E[X_i] = mu_i$, and let $Y_n = X_1+...+X_n$. I want to show that if $sum_n mu_n = infty $ then $Y_n/E[Y_n] rightarrow 1$ almost surly.
What I do know is that if $X_1,...$ are independent, and $Eleft[X^4right] < infty$, then $Y_n/n rightarrow E[X]$ a.s.* So What I tried is to center the random variables: let $C_n := X_n-mu_n$. The $C$'s are independent, $E[C_n^4]< infty, E[C_n] = 0$, which means:
$frac{C_1 +...+C_n}{n} rightarrow 0$ a.s., or $frac{sum X_i - sum mu_i}{n} rightarrow 0$ a.s. which, I think, completes the proof.
However I am not sure why the requirement $sum_n mu_n = infty $ is necessary, so I suspect this proof is incorrect. Is it?
Edit: This argument is incorrect since the theorem requires $E[C^4]$ to be uniformly bounded, not just bounded. Any ideas?
- This is the statement of the theorem from "Probability with Martingales"
probability probability-theory probability-distributions poisson-distribution law-of-large-numbers
probability probability-theory probability-distributions poisson-distribution law-of-large-numbers
edited Dec 16 '18 at 13:51
SomeoneHAHA
asked Dec 16 '18 at 12:49
SomeoneHAHASomeoneHAHA
83
83
1
$begingroup$
You cannot apply the result you recall since it requires the increments are identically distributed -- which is not true in your case (except if $mu_n$ does not depend on $mu$).
$endgroup$
– Did
Dec 16 '18 at 13:04
$begingroup$
To see why the $sum_nmu_n=infty$ requirement is needed consider what happens if $mu_1=1$ and $mu_n=0$ for $n>1$.
$endgroup$
– kimchi lover
Dec 16 '18 at 13:07
$begingroup$
@Did - The result I cited does not require i.d. See "Probability with martingales" Chapter 7
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 13:15
$begingroup$
Except you misquoted heavily.
$endgroup$
– Did
Dec 16 '18 at 13:17
$begingroup$
@kimchilover If $mu_n = 0$ it would mean that $X_n = 0$, so I am not sure where is the problem
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 13:17
|
show 4 more comments
1
$begingroup$
You cannot apply the result you recall since it requires the increments are identically distributed -- which is not true in your case (except if $mu_n$ does not depend on $mu$).
$endgroup$
– Did
Dec 16 '18 at 13:04
$begingroup$
To see why the $sum_nmu_n=infty$ requirement is needed consider what happens if $mu_1=1$ and $mu_n=0$ for $n>1$.
$endgroup$
– kimchi lover
Dec 16 '18 at 13:07
$begingroup$
@Did - The result I cited does not require i.d. See "Probability with martingales" Chapter 7
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 13:15
$begingroup$
Except you misquoted heavily.
$endgroup$
– Did
Dec 16 '18 at 13:17
$begingroup$
@kimchilover If $mu_n = 0$ it would mean that $X_n = 0$, so I am not sure where is the problem
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 13:17
1
1
$begingroup$
You cannot apply the result you recall since it requires the increments are identically distributed -- which is not true in your case (except if $mu_n$ does not depend on $mu$).
$endgroup$
– Did
Dec 16 '18 at 13:04
$begingroup$
You cannot apply the result you recall since it requires the increments are identically distributed -- which is not true in your case (except if $mu_n$ does not depend on $mu$).
$endgroup$
– Did
Dec 16 '18 at 13:04
$begingroup$
To see why the $sum_nmu_n=infty$ requirement is needed consider what happens if $mu_1=1$ and $mu_n=0$ for $n>1$.
$endgroup$
– kimchi lover
Dec 16 '18 at 13:07
$begingroup$
To see why the $sum_nmu_n=infty$ requirement is needed consider what happens if $mu_1=1$ and $mu_n=0$ for $n>1$.
$endgroup$
– kimchi lover
Dec 16 '18 at 13:07
$begingroup$
@Did - The result I cited does not require i.d. See "Probability with martingales" Chapter 7
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 13:15
$begingroup$
@Did - The result I cited does not require i.d. See "Probability with martingales" Chapter 7
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 13:15
$begingroup$
Except you misquoted heavily.
$endgroup$
– Did
Dec 16 '18 at 13:17
$begingroup$
Except you misquoted heavily.
$endgroup$
– Did
Dec 16 '18 at 13:17
$begingroup$
@kimchilover If $mu_n = 0$ it would mean that $X_n = 0$, so I am not sure where is the problem
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 13:17
$begingroup$
@kimchilover If $mu_n = 0$ it would mean that $X_n = 0$, so I am not sure where is the problem
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 13:17
|
show 4 more comments
1 Answer
1
active
oldest
votes
$begingroup$
If, in your argument, $M=sum_n mu_n<infty$ then your $Y_n$ converge in distribution to a Poisson rv. with expectation $M$, and your ratio $Y_n/EY_n$ has a non trivial limit distribution, violating a.s. convergence to a constant.
And, the theorem you quote needs a uniform 4th moment bound $EX_k^4le K$, which need not hold given your hypotheses.
A better way to prove your result might be to write your $Y_n$ as $Y_n=Y(M_n)$, where $M_n=sum_{tle n} mu_t$ and where $Y(t)$ is a Poisson process, as described in the wikipedia article. You might be able to show $Y(t)/tto 1$ almost surely.
Alternatively, you could use your argument with the added hypothesis that $mu_nle1$ for all $n$ and then use that to prove the general result by representing each $mu_n$ as a sum of quantities that are individually bounded by $1$, and your corresponding $Y_n$ as sums of independent Poissons whose expectations are bounded and add up to the right thing.
$endgroup$
$begingroup$
I see. So: the overall argument is correct, except the punch: $C_1+...+C_n /n rightarrow 0$ implies the claim only if $M = infty$, or should I change the entire argument? The comments in the original question made me completely not sure about is correctness. Thanks!
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 13:38
$begingroup$
Re the edit: I see now that my argument is not true due to the uniform bounded requirement. Do you think that there is a proof which is not going through Poisson process?
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 13:49
$begingroup$
I suppose there could be a non-Poisson process proof, but it would probably be ugly, like an apparatus designed by a lawyer to not infringe on a particular patent.
$endgroup$
– kimchi lover
Dec 16 '18 at 13:58
$begingroup$
Thanks. May you elaborate more on this way of proof? I am not familiar with Poisson processes, so I read about it but still have no idea how to use it here
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 14:55
add a comment |
Your Answer
StackExchange.ifUsing("editor", function () {
return StackExchange.using("mathjaxEditing", function () {
StackExchange.MarkdownEditor.creationCallbacks.add(function (editor, postfix) {
StackExchange.mathjaxEditing.prepareWmdForMathJax(editor, postfix, [["$", "$"], ["\\(","\\)"]]);
});
});
}, "mathjax-editing");
StackExchange.ready(function() {
var channelOptions = {
tags: "".split(" "),
id: "69"
};
initTagRenderer("".split(" "), "".split(" "), channelOptions);
StackExchange.using("externalEditor", function() {
// Have to fire editor after snippets, if snippets enabled
if (StackExchange.settings.snippets.snippetsEnabled) {
StackExchange.using("snippets", function() {
createEditor();
});
}
else {
createEditor();
}
});
function createEditor() {
StackExchange.prepareEditor({
heartbeatType: 'answer',
autoActivateHeartbeat: false,
convertImagesToLinks: true,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: 10,
bindNavPrevention: true,
postfix: "",
imageUploader: {
brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
allowUrls: true
},
noCode: true, onDemand: true,
discardSelector: ".discard-answer"
,immediatelyShowMarkdownHelp:true
});
}
});
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f3042579%2fstrong-law-of-large-numbers-for-poisson-rvs-with-different-parameter%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
$begingroup$
If, in your argument, $M=sum_n mu_n<infty$ then your $Y_n$ converge in distribution to a Poisson rv. with expectation $M$, and your ratio $Y_n/EY_n$ has a non trivial limit distribution, violating a.s. convergence to a constant.
And, the theorem you quote needs a uniform 4th moment bound $EX_k^4le K$, which need not hold given your hypotheses.
A better way to prove your result might be to write your $Y_n$ as $Y_n=Y(M_n)$, where $M_n=sum_{tle n} mu_t$ and where $Y(t)$ is a Poisson process, as described in the wikipedia article. You might be able to show $Y(t)/tto 1$ almost surely.
Alternatively, you could use your argument with the added hypothesis that $mu_nle1$ for all $n$ and then use that to prove the general result by representing each $mu_n$ as a sum of quantities that are individually bounded by $1$, and your corresponding $Y_n$ as sums of independent Poissons whose expectations are bounded and add up to the right thing.
$endgroup$
$begingroup$
I see. So: the overall argument is correct, except the punch: $C_1+...+C_n /n rightarrow 0$ implies the claim only if $M = infty$, or should I change the entire argument? The comments in the original question made me completely not sure about is correctness. Thanks!
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 13:38
$begingroup$
Re the edit: I see now that my argument is not true due to the uniform bounded requirement. Do you think that there is a proof which is not going through Poisson process?
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 13:49
$begingroup$
I suppose there could be a non-Poisson process proof, but it would probably be ugly, like an apparatus designed by a lawyer to not infringe on a particular patent.
$endgroup$
– kimchi lover
Dec 16 '18 at 13:58
$begingroup$
Thanks. May you elaborate more on this way of proof? I am not familiar with Poisson processes, so I read about it but still have no idea how to use it here
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 14:55
add a comment |
$begingroup$
If, in your argument, $M=sum_n mu_n<infty$ then your $Y_n$ converge in distribution to a Poisson rv. with expectation $M$, and your ratio $Y_n/EY_n$ has a non trivial limit distribution, violating a.s. convergence to a constant.
And, the theorem you quote needs a uniform 4th moment bound $EX_k^4le K$, which need not hold given your hypotheses.
A better way to prove your result might be to write your $Y_n$ as $Y_n=Y(M_n)$, where $M_n=sum_{tle n} mu_t$ and where $Y(t)$ is a Poisson process, as described in the wikipedia article. You might be able to show $Y(t)/tto 1$ almost surely.
Alternatively, you could use your argument with the added hypothesis that $mu_nle1$ for all $n$ and then use that to prove the general result by representing each $mu_n$ as a sum of quantities that are individually bounded by $1$, and your corresponding $Y_n$ as sums of independent Poissons whose expectations are bounded and add up to the right thing.
$endgroup$
$begingroup$
I see. So: the overall argument is correct, except the punch: $C_1+...+C_n /n rightarrow 0$ implies the claim only if $M = infty$, or should I change the entire argument? The comments in the original question made me completely not sure about is correctness. Thanks!
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 13:38
$begingroup$
Re the edit: I see now that my argument is not true due to the uniform bounded requirement. Do you think that there is a proof which is not going through Poisson process?
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 13:49
$begingroup$
I suppose there could be a non-Poisson process proof, but it would probably be ugly, like an apparatus designed by a lawyer to not infringe on a particular patent.
$endgroup$
– kimchi lover
Dec 16 '18 at 13:58
$begingroup$
Thanks. May you elaborate more on this way of proof? I am not familiar with Poisson processes, so I read about it but still have no idea how to use it here
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 14:55
add a comment |
$begingroup$
If, in your argument, $M=sum_n mu_n<infty$ then your $Y_n$ converge in distribution to a Poisson rv. with expectation $M$, and your ratio $Y_n/EY_n$ has a non trivial limit distribution, violating a.s. convergence to a constant.
And, the theorem you quote needs a uniform 4th moment bound $EX_k^4le K$, which need not hold given your hypotheses.
A better way to prove your result might be to write your $Y_n$ as $Y_n=Y(M_n)$, where $M_n=sum_{tle n} mu_t$ and where $Y(t)$ is a Poisson process, as described in the wikipedia article. You might be able to show $Y(t)/tto 1$ almost surely.
Alternatively, you could use your argument with the added hypothesis that $mu_nle1$ for all $n$ and then use that to prove the general result by representing each $mu_n$ as a sum of quantities that are individually bounded by $1$, and your corresponding $Y_n$ as sums of independent Poissons whose expectations are bounded and add up to the right thing.
$endgroup$
If, in your argument, $M=sum_n mu_n<infty$ then your $Y_n$ converge in distribution to a Poisson rv. with expectation $M$, and your ratio $Y_n/EY_n$ has a non trivial limit distribution, violating a.s. convergence to a constant.
And, the theorem you quote needs a uniform 4th moment bound $EX_k^4le K$, which need not hold given your hypotheses.
A better way to prove your result might be to write your $Y_n$ as $Y_n=Y(M_n)$, where $M_n=sum_{tle n} mu_t$ and where $Y(t)$ is a Poisson process, as described in the wikipedia article. You might be able to show $Y(t)/tto 1$ almost surely.
Alternatively, you could use your argument with the added hypothesis that $mu_nle1$ for all $n$ and then use that to prove the general result by representing each $mu_n$ as a sum of quantities that are individually bounded by $1$, and your corresponding $Y_n$ as sums of independent Poissons whose expectations are bounded and add up to the right thing.
edited Dec 16 '18 at 15:03
answered Dec 16 '18 at 13:23
kimchi loverkimchi lover
9,70631128
9,70631128
$begingroup$
I see. So: the overall argument is correct, except the punch: $C_1+...+C_n /n rightarrow 0$ implies the claim only if $M = infty$, or should I change the entire argument? The comments in the original question made me completely not sure about is correctness. Thanks!
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 13:38
$begingroup$
Re the edit: I see now that my argument is not true due to the uniform bounded requirement. Do you think that there is a proof which is not going through Poisson process?
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 13:49
$begingroup$
I suppose there could be a non-Poisson process proof, but it would probably be ugly, like an apparatus designed by a lawyer to not infringe on a particular patent.
$endgroup$
– kimchi lover
Dec 16 '18 at 13:58
$begingroup$
Thanks. May you elaborate more on this way of proof? I am not familiar with Poisson processes, so I read about it but still have no idea how to use it here
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 14:55
add a comment |
$begingroup$
I see. So: the overall argument is correct, except the punch: $C_1+...+C_n /n rightarrow 0$ implies the claim only if $M = infty$, or should I change the entire argument? The comments in the original question made me completely not sure about is correctness. Thanks!
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 13:38
$begingroup$
Re the edit: I see now that my argument is not true due to the uniform bounded requirement. Do you think that there is a proof which is not going through Poisson process?
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 13:49
$begingroup$
I suppose there could be a non-Poisson process proof, but it would probably be ugly, like an apparatus designed by a lawyer to not infringe on a particular patent.
$endgroup$
– kimchi lover
Dec 16 '18 at 13:58
$begingroup$
Thanks. May you elaborate more on this way of proof? I am not familiar with Poisson processes, so I read about it but still have no idea how to use it here
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 14:55
$begingroup$
I see. So: the overall argument is correct, except the punch: $C_1+...+C_n /n rightarrow 0$ implies the claim only if $M = infty$, or should I change the entire argument? The comments in the original question made me completely not sure about is correctness. Thanks!
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 13:38
$begingroup$
I see. So: the overall argument is correct, except the punch: $C_1+...+C_n /n rightarrow 0$ implies the claim only if $M = infty$, or should I change the entire argument? The comments in the original question made me completely not sure about is correctness. Thanks!
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 13:38
$begingroup$
Re the edit: I see now that my argument is not true due to the uniform bounded requirement. Do you think that there is a proof which is not going through Poisson process?
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 13:49
$begingroup$
Re the edit: I see now that my argument is not true due to the uniform bounded requirement. Do you think that there is a proof which is not going through Poisson process?
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 13:49
$begingroup$
I suppose there could be a non-Poisson process proof, but it would probably be ugly, like an apparatus designed by a lawyer to not infringe on a particular patent.
$endgroup$
– kimchi lover
Dec 16 '18 at 13:58
$begingroup$
I suppose there could be a non-Poisson process proof, but it would probably be ugly, like an apparatus designed by a lawyer to not infringe on a particular patent.
$endgroup$
– kimchi lover
Dec 16 '18 at 13:58
$begingroup$
Thanks. May you elaborate more on this way of proof? I am not familiar with Poisson processes, so I read about it but still have no idea how to use it here
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 14:55
$begingroup$
Thanks. May you elaborate more on this way of proof? I am not familiar with Poisson processes, so I read about it but still have no idea how to use it here
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 14:55
add a comment |
Thanks for contributing an answer to Mathematics Stack Exchange!
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
Use MathJax to format equations. MathJax reference.
To learn more, see our tips on writing great answers.
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f3042579%2fstrong-law-of-large-numbers-for-poisson-rvs-with-different-parameter%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
1
$begingroup$
You cannot apply the result you recall since it requires the increments are identically distributed -- which is not true in your case (except if $mu_n$ does not depend on $mu$).
$endgroup$
– Did
Dec 16 '18 at 13:04
$begingroup$
To see why the $sum_nmu_n=infty$ requirement is needed consider what happens if $mu_1=1$ and $mu_n=0$ for $n>1$.
$endgroup$
– kimchi lover
Dec 16 '18 at 13:07
$begingroup$
@Did - The result I cited does not require i.d. See "Probability with martingales" Chapter 7
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 13:15
$begingroup$
Except you misquoted heavily.
$endgroup$
– Did
Dec 16 '18 at 13:17
$begingroup$
@kimchilover If $mu_n = 0$ it would mean that $X_n = 0$, so I am not sure where is the problem
$endgroup$
– SomeoneHAHA
Dec 16 '18 at 13:17