Existence of weak limit of measuresWhen weak convergence implies moment convergence?weak*-limit of bounded sequence of measuresMoments and weak convergence of probability measures IIAre vague convergence and weak convergence of measures both weak* convergence?Techniques for determining whether the weak limit of an absolutely continuous sequence of probability measures is absolutely continuous?Does weak convergence with uniformly bounded densities imply absolute continuity of the limit?Does convergence of $lim_n rightarrow infty int h dmu_n$ for all continuous, bounded $h$ imply weak convergence of $(mu_n)$?Weak convergence of linear combinations of Dirac measures to a signed measureWeak convergence of measures and boundednessweak-converging sequence of measures with ascending supports
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Existence of weak limit of measures
When weak convergence implies moment convergence?weak*-limit of bounded sequence of measuresMoments and weak convergence of probability measures IIAre vague convergence and weak convergence of measures both weak* convergence?Techniques for determining whether the weak limit of an absolutely continuous sequence of probability measures is absolutely continuous?Does weak convergence with uniformly bounded densities imply absolute continuity of the limit?Does convergence of $lim_n rightarrow infty int h dmu_n$ for all continuous, bounded $h$ imply weak convergence of $(mu_n)$?Weak convergence of linear combinations of Dirac measures to a signed measureWeak convergence of measures and boundednessweak-converging sequence of measures with ascending supports
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$begingroup$
Suppose $mu_n$ is a sequence of Borel probability measures on $mathbbC$ such that
$$
lim_n to infty int fdmu_n
$$
exists for all $f in C_b(mathbbC, mathbbR)$. Is it true that there exists a measure $mu$ such that
$$
int f dmu = lim_n to infty int fdmu_n?
$$
In other words, is there a measure $mu$ such that $mu_n to mu$ weakly?
In my problem, we can assume the support of the $mu_n$ is contained in the unit ball, if it helps.
analysis probability-theory measure-theory
$endgroup$
add a comment |
$begingroup$
Suppose $mu_n$ is a sequence of Borel probability measures on $mathbbC$ such that
$$
lim_n to infty int fdmu_n
$$
exists for all $f in C_b(mathbbC, mathbbR)$. Is it true that there exists a measure $mu$ such that
$$
int f dmu = lim_n to infty int fdmu_n?
$$
In other words, is there a measure $mu$ such that $mu_n to mu$ weakly?
In my problem, we can assume the support of the $mu_n$ is contained in the unit ball, if it helps.
analysis probability-theory measure-theory
$endgroup$
3
$begingroup$
The answers below are right, but another thing you might care about is whether the resulting $mu$ is actually a probability measure. In general, it doesn't have to be (imagine $mu_n$ spreading out to infinity, like a uniform distribution on the ball of radius $n$), but in your case it actually is, by just taking $f$ to be any continuous function with compact support that is $1$ on the unit ball.
$endgroup$
– J.G
Aug 11 at 22:49
add a comment |
$begingroup$
Suppose $mu_n$ is a sequence of Borel probability measures on $mathbbC$ such that
$$
lim_n to infty int fdmu_n
$$
exists for all $f in C_b(mathbbC, mathbbR)$. Is it true that there exists a measure $mu$ such that
$$
int f dmu = lim_n to infty int fdmu_n?
$$
In other words, is there a measure $mu$ such that $mu_n to mu$ weakly?
In my problem, we can assume the support of the $mu_n$ is contained in the unit ball, if it helps.
analysis probability-theory measure-theory
$endgroup$
Suppose $mu_n$ is a sequence of Borel probability measures on $mathbbC$ such that
$$
lim_n to infty int fdmu_n
$$
exists for all $f in C_b(mathbbC, mathbbR)$. Is it true that there exists a measure $mu$ such that
$$
int f dmu = lim_n to infty int fdmu_n?
$$
In other words, is there a measure $mu$ such that $mu_n to mu$ weakly?
In my problem, we can assume the support of the $mu_n$ is contained in the unit ball, if it helps.
analysis probability-theory measure-theory
analysis probability-theory measure-theory
edited Aug 11 at 22:33
WeakestTopology
asked Aug 11 at 22:23
WeakestTopologyWeakestTopology
5533 silver badges13 bronze badges
5533 silver badges13 bronze badges
3
$begingroup$
The answers below are right, but another thing you might care about is whether the resulting $mu$ is actually a probability measure. In general, it doesn't have to be (imagine $mu_n$ spreading out to infinity, like a uniform distribution on the ball of radius $n$), but in your case it actually is, by just taking $f$ to be any continuous function with compact support that is $1$ on the unit ball.
$endgroup$
– J.G
Aug 11 at 22:49
add a comment |
3
$begingroup$
The answers below are right, but another thing you might care about is whether the resulting $mu$ is actually a probability measure. In general, it doesn't have to be (imagine $mu_n$ spreading out to infinity, like a uniform distribution on the ball of radius $n$), but in your case it actually is, by just taking $f$ to be any continuous function with compact support that is $1$ on the unit ball.
$endgroup$
– J.G
Aug 11 at 22:49
3
3
$begingroup$
The answers below are right, but another thing you might care about is whether the resulting $mu$ is actually a probability measure. In general, it doesn't have to be (imagine $mu_n$ spreading out to infinity, like a uniform distribution on the ball of radius $n$), but in your case it actually is, by just taking $f$ to be any continuous function with compact support that is $1$ on the unit ball.
$endgroup$
– J.G
Aug 11 at 22:49
$begingroup$
The answers below are right, but another thing you might care about is whether the resulting $mu$ is actually a probability measure. In general, it doesn't have to be (imagine $mu_n$ spreading out to infinity, like a uniform distribution on the ball of radius $n$), but in your case it actually is, by just taking $f$ to be any continuous function with compact support that is $1$ on the unit ball.
$endgroup$
– J.G
Aug 11 at 22:49
add a comment |
2 Answers
2
active
oldest
votes
$begingroup$
Yes! Consider the restriction to the space of continuous functions with compact support, denoted by $C_c(mathbbC, mathbbR)$. Now define $$L(f):= lim_nrightarrow infty int f , dmu_nqquad , , fin C_c(mathbbC, mathbbR).$$
It is straightforward to check that $L$ defines a bounded linear functional on $C_c(mathbbC,mathbbR)$. Indeed, since the $leftmu_nright$'s are Borel probability measures on $mathbbC$, we have
$$lvert L(f) rvert leq lvert lvert frvert rvert_infty$$ Hence by the Riesz–Markov–Kakutani representation theorem, there exists a unique Borel measure $mu$,with total variation-norm less than 1, such that $$L(f) = int f , dmu qquad forall fin C_c(mathbbC,mathbbR).$$
In fact, the integral is well-defined for all $C_b(mathbbC, mathbbR)$ as well.
$endgroup$
add a comment |
$begingroup$
Define $l: C_c(mathbbC,mathbbR) to mathbbR$ by $l(f) = lim_n to infty int fdmu_n$. Then $l$ is a positive, continuous linear functional, so by Riesz representation theorem, there is some measure $mu$ with $l(f) = int fdmu$.
$endgroup$
add a comment |
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2 Answers
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2 Answers
2
active
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$begingroup$
Yes! Consider the restriction to the space of continuous functions with compact support, denoted by $C_c(mathbbC, mathbbR)$. Now define $$L(f):= lim_nrightarrow infty int f , dmu_nqquad , , fin C_c(mathbbC, mathbbR).$$
It is straightforward to check that $L$ defines a bounded linear functional on $C_c(mathbbC,mathbbR)$. Indeed, since the $leftmu_nright$'s are Borel probability measures on $mathbbC$, we have
$$lvert L(f) rvert leq lvert lvert frvert rvert_infty$$ Hence by the Riesz–Markov–Kakutani representation theorem, there exists a unique Borel measure $mu$,with total variation-norm less than 1, such that $$L(f) = int f , dmu qquad forall fin C_c(mathbbC,mathbbR).$$
In fact, the integral is well-defined for all $C_b(mathbbC, mathbbR)$ as well.
$endgroup$
add a comment |
$begingroup$
Yes! Consider the restriction to the space of continuous functions with compact support, denoted by $C_c(mathbbC, mathbbR)$. Now define $$L(f):= lim_nrightarrow infty int f , dmu_nqquad , , fin C_c(mathbbC, mathbbR).$$
It is straightforward to check that $L$ defines a bounded linear functional on $C_c(mathbbC,mathbbR)$. Indeed, since the $leftmu_nright$'s are Borel probability measures on $mathbbC$, we have
$$lvert L(f) rvert leq lvert lvert frvert rvert_infty$$ Hence by the Riesz–Markov–Kakutani representation theorem, there exists a unique Borel measure $mu$,with total variation-norm less than 1, such that $$L(f) = int f , dmu qquad forall fin C_c(mathbbC,mathbbR).$$
In fact, the integral is well-defined for all $C_b(mathbbC, mathbbR)$ as well.
$endgroup$
add a comment |
$begingroup$
Yes! Consider the restriction to the space of continuous functions with compact support, denoted by $C_c(mathbbC, mathbbR)$. Now define $$L(f):= lim_nrightarrow infty int f , dmu_nqquad , , fin C_c(mathbbC, mathbbR).$$
It is straightforward to check that $L$ defines a bounded linear functional on $C_c(mathbbC,mathbbR)$. Indeed, since the $leftmu_nright$'s are Borel probability measures on $mathbbC$, we have
$$lvert L(f) rvert leq lvert lvert frvert rvert_infty$$ Hence by the Riesz–Markov–Kakutani representation theorem, there exists a unique Borel measure $mu$,with total variation-norm less than 1, such that $$L(f) = int f , dmu qquad forall fin C_c(mathbbC,mathbbR).$$
In fact, the integral is well-defined for all $C_b(mathbbC, mathbbR)$ as well.
$endgroup$
Yes! Consider the restriction to the space of continuous functions with compact support, denoted by $C_c(mathbbC, mathbbR)$. Now define $$L(f):= lim_nrightarrow infty int f , dmu_nqquad , , fin C_c(mathbbC, mathbbR).$$
It is straightforward to check that $L$ defines a bounded linear functional on $C_c(mathbbC,mathbbR)$. Indeed, since the $leftmu_nright$'s are Borel probability measures on $mathbbC$, we have
$$lvert L(f) rvert leq lvert lvert frvert rvert_infty$$ Hence by the Riesz–Markov–Kakutani representation theorem, there exists a unique Borel measure $mu$,with total variation-norm less than 1, such that $$L(f) = int f , dmu qquad forall fin C_c(mathbbC,mathbbR).$$
In fact, the integral is well-defined for all $C_b(mathbbC, mathbbR)$ as well.
answered Aug 11 at 22:40
TheOscillatorTheOscillator
2,2341 gold badge8 silver badges18 bronze badges
2,2341 gold badge8 silver badges18 bronze badges
add a comment |
add a comment |
$begingroup$
Define $l: C_c(mathbbC,mathbbR) to mathbbR$ by $l(f) = lim_n to infty int fdmu_n$. Then $l$ is a positive, continuous linear functional, so by Riesz representation theorem, there is some measure $mu$ with $l(f) = int fdmu$.
$endgroup$
add a comment |
$begingroup$
Define $l: C_c(mathbbC,mathbbR) to mathbbR$ by $l(f) = lim_n to infty int fdmu_n$. Then $l$ is a positive, continuous linear functional, so by Riesz representation theorem, there is some measure $mu$ with $l(f) = int fdmu$.
$endgroup$
add a comment |
$begingroup$
Define $l: C_c(mathbbC,mathbbR) to mathbbR$ by $l(f) = lim_n to infty int fdmu_n$. Then $l$ is a positive, continuous linear functional, so by Riesz representation theorem, there is some measure $mu$ with $l(f) = int fdmu$.
$endgroup$
Define $l: C_c(mathbbC,mathbbR) to mathbbR$ by $l(f) = lim_n to infty int fdmu_n$. Then $l$ is a positive, continuous linear functional, so by Riesz representation theorem, there is some measure $mu$ with $l(f) = int fdmu$.
edited Aug 12 at 13:20
answered Aug 11 at 22:37
mathworker21mathworker21
11.1k1 gold badge10 silver badges31 bronze badges
11.1k1 gold badge10 silver badges31 bronze badges
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The answers below are right, but another thing you might care about is whether the resulting $mu$ is actually a probability measure. In general, it doesn't have to be (imagine $mu_n$ spreading out to infinity, like a uniform distribution on the ball of radius $n$), but in your case it actually is, by just taking $f$ to be any continuous function with compact support that is $1$ on the unit ball.
$endgroup$
– J.G
Aug 11 at 22:49