Central Limit Theorem for not identical distributed but independent centered random variables with variance...
$begingroup$
so let's assume we have independent random variables $X_1,X_2, X_3, ldots$ with
$$mathbb{E}[X_k]=0 mbox{ and } mathbb{Var}[X_k]=sigma_k^2=1 quad forall kinmathbb{N}. $$
We define $$s_n^2:= sum_{k=1}^n mathbb{E}[(X_k-mathbb{E}[X_k])^2]=sum_{k=1}^nsigma_k^2=n.$$
Now we check Lindenberg's condition: So for $varepsilon>0$ we must check
$$limlimits_{nrightarrow infty} frac{1}{s_n^2}sum_{k=1}^n mathbb{E}[(X_k-mathbb{E}[X_k])^2 cdot mathbf{1}_{|X_k| > varepsilon s_n^2} ]
=limlimits_{nrightarrow infty} frac{1}{n} sum_{k=1}^n mathbb{E}[X_k^2 cdot mathbf{1}_{|X_k| > varepsilon n} ].$$
We know,
$$mathbb{E}[X_k^2 ]=1,$$
so
$$mathbb{E}[X_k^2 cdot mathbf{1}_{|X_k| > varepsilon n} ]$$
converges quicker than $$frac{1}{n},$$
whch means we find an $Ninmathbb{N}$ such that for every $ngeq N$ we have
$$mathbb{E}[X_k^2 cdot mathbf{1}_{|X_k| > varepsilon n} ]< frac{1}{n}, $$
which means for every $varepsilon>0$ we have
$$limlimits_{nrightarrow infty} frac{1}{n} sum_{k=1}^n mathbb{E}[X_k^2 cdot mathbf{1}_{|X_k| > varepsilon n} ] leq limlimits_{nrightarrow infty} frac{N}{n} + frac{1}{n} sum_{k=N+1}^n mathbb{E}[X_k^2 cdot mathbf{1}_{|X_k| > varepsilon n} ]< limlimits_{nrightarrow infty} frac{N}{n} + + frac{1}{n^2 }=0,$$
so we know that the Central Limit Theorem holds.
Is that right?
Edit:
What we really need is uniform integrability of ${ X_k^2: kinmathbb{N}} $$ and that gives us that Lindeberg holds.
Otherwise we can construct $X_j$ with $$P(X_j =-j^2 )=P(X_j =j^2 ) = j^{-4}/2$$ and Lindeberg does not hold!
probability-theory central-limit-theorem
$endgroup$
add a comment |
$begingroup$
so let's assume we have independent random variables $X_1,X_2, X_3, ldots$ with
$$mathbb{E}[X_k]=0 mbox{ and } mathbb{Var}[X_k]=sigma_k^2=1 quad forall kinmathbb{N}. $$
We define $$s_n^2:= sum_{k=1}^n mathbb{E}[(X_k-mathbb{E}[X_k])^2]=sum_{k=1}^nsigma_k^2=n.$$
Now we check Lindenberg's condition: So for $varepsilon>0$ we must check
$$limlimits_{nrightarrow infty} frac{1}{s_n^2}sum_{k=1}^n mathbb{E}[(X_k-mathbb{E}[X_k])^2 cdot mathbf{1}_{|X_k| > varepsilon s_n^2} ]
=limlimits_{nrightarrow infty} frac{1}{n} sum_{k=1}^n mathbb{E}[X_k^2 cdot mathbf{1}_{|X_k| > varepsilon n} ].$$
We know,
$$mathbb{E}[X_k^2 ]=1,$$
so
$$mathbb{E}[X_k^2 cdot mathbf{1}_{|X_k| > varepsilon n} ]$$
converges quicker than $$frac{1}{n},$$
whch means we find an $Ninmathbb{N}$ such that for every $ngeq N$ we have
$$mathbb{E}[X_k^2 cdot mathbf{1}_{|X_k| > varepsilon n} ]< frac{1}{n}, $$
which means for every $varepsilon>0$ we have
$$limlimits_{nrightarrow infty} frac{1}{n} sum_{k=1}^n mathbb{E}[X_k^2 cdot mathbf{1}_{|X_k| > varepsilon n} ] leq limlimits_{nrightarrow infty} frac{N}{n} + frac{1}{n} sum_{k=N+1}^n mathbb{E}[X_k^2 cdot mathbf{1}_{|X_k| > varepsilon n} ]< limlimits_{nrightarrow infty} frac{N}{n} + + frac{1}{n^2 }=0,$$
so we know that the Central Limit Theorem holds.
Is that right?
Edit:
What we really need is uniform integrability of ${ X_k^2: kinmathbb{N}} $$ and that gives us that Lindeberg holds.
Otherwise we can construct $X_j$ with $$P(X_j =-j^2 )=P(X_j =j^2 ) = j^{-4}/2$$ and Lindeberg does not hold!
probability-theory central-limit-theorem
$endgroup$
add a comment |
$begingroup$
so let's assume we have independent random variables $X_1,X_2, X_3, ldots$ with
$$mathbb{E}[X_k]=0 mbox{ and } mathbb{Var}[X_k]=sigma_k^2=1 quad forall kinmathbb{N}. $$
We define $$s_n^2:= sum_{k=1}^n mathbb{E}[(X_k-mathbb{E}[X_k])^2]=sum_{k=1}^nsigma_k^2=n.$$
Now we check Lindenberg's condition: So for $varepsilon>0$ we must check
$$limlimits_{nrightarrow infty} frac{1}{s_n^2}sum_{k=1}^n mathbb{E}[(X_k-mathbb{E}[X_k])^2 cdot mathbf{1}_{|X_k| > varepsilon s_n^2} ]
=limlimits_{nrightarrow infty} frac{1}{n} sum_{k=1}^n mathbb{E}[X_k^2 cdot mathbf{1}_{|X_k| > varepsilon n} ].$$
We know,
$$mathbb{E}[X_k^2 ]=1,$$
so
$$mathbb{E}[X_k^2 cdot mathbf{1}_{|X_k| > varepsilon n} ]$$
converges quicker than $$frac{1}{n},$$
whch means we find an $Ninmathbb{N}$ such that for every $ngeq N$ we have
$$mathbb{E}[X_k^2 cdot mathbf{1}_{|X_k| > varepsilon n} ]< frac{1}{n}, $$
which means for every $varepsilon>0$ we have
$$limlimits_{nrightarrow infty} frac{1}{n} sum_{k=1}^n mathbb{E}[X_k^2 cdot mathbf{1}_{|X_k| > varepsilon n} ] leq limlimits_{nrightarrow infty} frac{N}{n} + frac{1}{n} sum_{k=N+1}^n mathbb{E}[X_k^2 cdot mathbf{1}_{|X_k| > varepsilon n} ]< limlimits_{nrightarrow infty} frac{N}{n} + + frac{1}{n^2 }=0,$$
so we know that the Central Limit Theorem holds.
Is that right?
Edit:
What we really need is uniform integrability of ${ X_k^2: kinmathbb{N}} $$ and that gives us that Lindeberg holds.
Otherwise we can construct $X_j$ with $$P(X_j =-j^2 )=P(X_j =j^2 ) = j^{-4}/2$$ and Lindeberg does not hold!
probability-theory central-limit-theorem
$endgroup$
so let's assume we have independent random variables $X_1,X_2, X_3, ldots$ with
$$mathbb{E}[X_k]=0 mbox{ and } mathbb{Var}[X_k]=sigma_k^2=1 quad forall kinmathbb{N}. $$
We define $$s_n^2:= sum_{k=1}^n mathbb{E}[(X_k-mathbb{E}[X_k])^2]=sum_{k=1}^nsigma_k^2=n.$$
Now we check Lindenberg's condition: So for $varepsilon>0$ we must check
$$limlimits_{nrightarrow infty} frac{1}{s_n^2}sum_{k=1}^n mathbb{E}[(X_k-mathbb{E}[X_k])^2 cdot mathbf{1}_{|X_k| > varepsilon s_n^2} ]
=limlimits_{nrightarrow infty} frac{1}{n} sum_{k=1}^n mathbb{E}[X_k^2 cdot mathbf{1}_{|X_k| > varepsilon n} ].$$
We know,
$$mathbb{E}[X_k^2 ]=1,$$
so
$$mathbb{E}[X_k^2 cdot mathbf{1}_{|X_k| > varepsilon n} ]$$
converges quicker than $$frac{1}{n},$$
whch means we find an $Ninmathbb{N}$ such that for every $ngeq N$ we have
$$mathbb{E}[X_k^2 cdot mathbf{1}_{|X_k| > varepsilon n} ]< frac{1}{n}, $$
which means for every $varepsilon>0$ we have
$$limlimits_{nrightarrow infty} frac{1}{n} sum_{k=1}^n mathbb{E}[X_k^2 cdot mathbf{1}_{|X_k| > varepsilon n} ] leq limlimits_{nrightarrow infty} frac{N}{n} + frac{1}{n} sum_{k=N+1}^n mathbb{E}[X_k^2 cdot mathbf{1}_{|X_k| > varepsilon n} ]< limlimits_{nrightarrow infty} frac{N}{n} + + frac{1}{n^2 }=0,$$
so we know that the Central Limit Theorem holds.
Is that right?
Edit:
What we really need is uniform integrability of ${ X_k^2: kinmathbb{N}} $$ and that gives us that Lindeberg holds.
Otherwise we can construct $X_j$ with $$P(X_j =-j^2 )=P(X_j =j^2 ) = j^{-4}/2$$ and Lindeberg does not hold!
probability-theory central-limit-theorem
probability-theory central-limit-theorem
edited Dec 13 '18 at 2:50
cptflint
asked Dec 11 '18 at 16:34
cptflintcptflint
208
208
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1 Answer
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$begingroup$
It may be not true that $mathbb{E}left[X_k^2 cdot mathbf{1}_{|X_k| > varepsilon n} right]$ is of order $1/n$. For example, if $X_1$ is such that its tail $Pr(leftlvert X_1rightrvert >t)sim t^{-2}(log t)^{-2}$, then $mathbb{E}[X_1^2 cdot mathbf{1}_{|X_1| > varepsilon n} ]$ is of order $1/log n$.
Note that it would suffices to have uniform integrability, that is,
$$
lim_{Rto +infty}sup_{kgeqslant 1}mathbb{E}left[X_k^2 cdot mathbf{1}_{|X_k| > R} right]=0.
$$
Otherwise, the are counter-examples.
$endgroup$
$begingroup$
I think we have uniform integrability, because $sigma_k^2=1$, but we haven't unform integrability of the family $X_k^2$, right?
$endgroup$
– cptflint
Dec 11 '18 at 23:24
$begingroup$
We indeed have integrability of each $X_k$ but in general not uniform integrability, unless you have other assumptions.
$endgroup$
– Davide Giraudo
Dec 12 '18 at 9:44
$begingroup$
I think we need $exists p>2, C>0: left[ forall k inN: EW[|X_k|^p ] leq C right]$, right? Then I have unfirom integrability of $X_k^2$, which means that we can use Lindeberg.
$endgroup$
– cptflint
Dec 12 '18 at 9:58
add a comment |
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$begingroup$
It may be not true that $mathbb{E}left[X_k^2 cdot mathbf{1}_{|X_k| > varepsilon n} right]$ is of order $1/n$. For example, if $X_1$ is such that its tail $Pr(leftlvert X_1rightrvert >t)sim t^{-2}(log t)^{-2}$, then $mathbb{E}[X_1^2 cdot mathbf{1}_{|X_1| > varepsilon n} ]$ is of order $1/log n$.
Note that it would suffices to have uniform integrability, that is,
$$
lim_{Rto +infty}sup_{kgeqslant 1}mathbb{E}left[X_k^2 cdot mathbf{1}_{|X_k| > R} right]=0.
$$
Otherwise, the are counter-examples.
$endgroup$
$begingroup$
I think we have uniform integrability, because $sigma_k^2=1$, but we haven't unform integrability of the family $X_k^2$, right?
$endgroup$
– cptflint
Dec 11 '18 at 23:24
$begingroup$
We indeed have integrability of each $X_k$ but in general not uniform integrability, unless you have other assumptions.
$endgroup$
– Davide Giraudo
Dec 12 '18 at 9:44
$begingroup$
I think we need $exists p>2, C>0: left[ forall k inN: EW[|X_k|^p ] leq C right]$, right? Then I have unfirom integrability of $X_k^2$, which means that we can use Lindeberg.
$endgroup$
– cptflint
Dec 12 '18 at 9:58
add a comment |
$begingroup$
It may be not true that $mathbb{E}left[X_k^2 cdot mathbf{1}_{|X_k| > varepsilon n} right]$ is of order $1/n$. For example, if $X_1$ is such that its tail $Pr(leftlvert X_1rightrvert >t)sim t^{-2}(log t)^{-2}$, then $mathbb{E}[X_1^2 cdot mathbf{1}_{|X_1| > varepsilon n} ]$ is of order $1/log n$.
Note that it would suffices to have uniform integrability, that is,
$$
lim_{Rto +infty}sup_{kgeqslant 1}mathbb{E}left[X_k^2 cdot mathbf{1}_{|X_k| > R} right]=0.
$$
Otherwise, the are counter-examples.
$endgroup$
$begingroup$
I think we have uniform integrability, because $sigma_k^2=1$, but we haven't unform integrability of the family $X_k^2$, right?
$endgroup$
– cptflint
Dec 11 '18 at 23:24
$begingroup$
We indeed have integrability of each $X_k$ but in general not uniform integrability, unless you have other assumptions.
$endgroup$
– Davide Giraudo
Dec 12 '18 at 9:44
$begingroup$
I think we need $exists p>2, C>0: left[ forall k inN: EW[|X_k|^p ] leq C right]$, right? Then I have unfirom integrability of $X_k^2$, which means that we can use Lindeberg.
$endgroup$
– cptflint
Dec 12 '18 at 9:58
add a comment |
$begingroup$
It may be not true that $mathbb{E}left[X_k^2 cdot mathbf{1}_{|X_k| > varepsilon n} right]$ is of order $1/n$. For example, if $X_1$ is such that its tail $Pr(leftlvert X_1rightrvert >t)sim t^{-2}(log t)^{-2}$, then $mathbb{E}[X_1^2 cdot mathbf{1}_{|X_1| > varepsilon n} ]$ is of order $1/log n$.
Note that it would suffices to have uniform integrability, that is,
$$
lim_{Rto +infty}sup_{kgeqslant 1}mathbb{E}left[X_k^2 cdot mathbf{1}_{|X_k| > R} right]=0.
$$
Otherwise, the are counter-examples.
$endgroup$
It may be not true that $mathbb{E}left[X_k^2 cdot mathbf{1}_{|X_k| > varepsilon n} right]$ is of order $1/n$. For example, if $X_1$ is such that its tail $Pr(leftlvert X_1rightrvert >t)sim t^{-2}(log t)^{-2}$, then $mathbb{E}[X_1^2 cdot mathbf{1}_{|X_1| > varepsilon n} ]$ is of order $1/log n$.
Note that it would suffices to have uniform integrability, that is,
$$
lim_{Rto +infty}sup_{kgeqslant 1}mathbb{E}left[X_k^2 cdot mathbf{1}_{|X_k| > R} right]=0.
$$
Otherwise, the are counter-examples.
edited Dec 13 '18 at 11:08
answered Dec 11 '18 at 19:22
Davide GiraudoDavide Giraudo
126k16150261
126k16150261
$begingroup$
I think we have uniform integrability, because $sigma_k^2=1$, but we haven't unform integrability of the family $X_k^2$, right?
$endgroup$
– cptflint
Dec 11 '18 at 23:24
$begingroup$
We indeed have integrability of each $X_k$ but in general not uniform integrability, unless you have other assumptions.
$endgroup$
– Davide Giraudo
Dec 12 '18 at 9:44
$begingroup$
I think we need $exists p>2, C>0: left[ forall k inN: EW[|X_k|^p ] leq C right]$, right? Then I have unfirom integrability of $X_k^2$, which means that we can use Lindeberg.
$endgroup$
– cptflint
Dec 12 '18 at 9:58
add a comment |
$begingroup$
I think we have uniform integrability, because $sigma_k^2=1$, but we haven't unform integrability of the family $X_k^2$, right?
$endgroup$
– cptflint
Dec 11 '18 at 23:24
$begingroup$
We indeed have integrability of each $X_k$ but in general not uniform integrability, unless you have other assumptions.
$endgroup$
– Davide Giraudo
Dec 12 '18 at 9:44
$begingroup$
I think we need $exists p>2, C>0: left[ forall k inN: EW[|X_k|^p ] leq C right]$, right? Then I have unfirom integrability of $X_k^2$, which means that we can use Lindeberg.
$endgroup$
– cptflint
Dec 12 '18 at 9:58
$begingroup$
I think we have uniform integrability, because $sigma_k^2=1$, but we haven't unform integrability of the family $X_k^2$, right?
$endgroup$
– cptflint
Dec 11 '18 at 23:24
$begingroup$
I think we have uniform integrability, because $sigma_k^2=1$, but we haven't unform integrability of the family $X_k^2$, right?
$endgroup$
– cptflint
Dec 11 '18 at 23:24
$begingroup$
We indeed have integrability of each $X_k$ but in general not uniform integrability, unless you have other assumptions.
$endgroup$
– Davide Giraudo
Dec 12 '18 at 9:44
$begingroup$
We indeed have integrability of each $X_k$ but in general not uniform integrability, unless you have other assumptions.
$endgroup$
– Davide Giraudo
Dec 12 '18 at 9:44
$begingroup$
I think we need $exists p>2, C>0: left[ forall k inN: EW[|X_k|^p ] leq C right]$, right? Then I have unfirom integrability of $X_k^2$, which means that we can use Lindeberg.
$endgroup$
– cptflint
Dec 12 '18 at 9:58
$begingroup$
I think we need $exists p>2, C>0: left[ forall k inN: EW[|X_k|^p ] leq C right]$, right? Then I have unfirom integrability of $X_k^2$, which means that we can use Lindeberg.
$endgroup$
– cptflint
Dec 12 '18 at 9:58
add a comment |
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