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Questions about abstract measure and Lebesgue integral theory. Also concerns such properties as measurability of maps and sets.
1
vote
a convolutional equation for the gaussian measure
No, by Bochner's Theorem the Fourier transform of a measure is positive definite and hence bounded.
1
vote
Mollifying a measure without changing its marginals
You can always formulate this problem as an optimization/feasibility problem and look for solutions. The conditions on the marginals gives two linear constraints: $$P_1\pi_\epsilon = \mu,\quad P_2\pi_ …
8
votes
2
answers
540
views
Is taking the positive part of a measure a continuous operation?
Here is question I tried to answer for some time - it seems to be straightforward, but I have trouble figuring it out.
Let $\Omega$ be a compact domain in $\mathbb{R}^n$. For any signed Borel measure …
2
votes
Accepted
Measures with finite mass relative to a fixed measure
The first natural thing that come to mind would be to consider the variation of the difference of the measure, i.e. assuming that the limit
$$
\lim_{R\to\infty}|\nu-\mu|(B_R)
$$
exists.
Considering t …
2
votes
The metric space associated to a measure space
Complementing the previous answer and comment: These metric is used in the context of shape optimization problems (in the case of $X$ a subset of $\mathbb{R}^d$ with the Lebesgue measure). In "Shapes …
1
vote
2
answers
114
views
Positive part of "outer sums" of measures
Here is a question about decomposition of measures in singular parts and in positive and negative parts.
$\newcommand{\RR}{\mathbb{R}}$
Let $\Omega_{1/2}$ be compact subsets of $\RR^d$ equipped signe …
2
votes
Accepted
Automating proofs via indicator functions?
I think, you are looking for a "monotone class argument", see the wikipedia entry for the monotone class theorem. In a nutshell, prove that the property holds for indicators and is preserved under fin …
1
vote
Accepted
sequences of plane measures converging to a singular one: terminology, etc
Whether or not the limit is singular (e.g. with respect to the Lebesgue measure), there are several notions of convergence for measures which can reflect this. Probably the most simple one is weak con …
3
votes
Accepted
Non-probabilist term for conditional expectation?
I quote "Functional Analysis for Probability and Stochastic Processes: An Introduction" by Adam Bobrowski, introduction to Chapter 3 "Conditional expectation":
$\newcommand{\cF}{\mathcal{F}}\newcomman …
0
votes
Absolutely continuous coupling of probability measures
If you work on compact domains instead of $\RR$ (or if you assume that all marginals have compact support), you can use couplings from regularized optimal transport: For $n=1$ (i.e. a coupling of just …
8
votes
1
answer
613
views
Completion of spaces of measures w.r.t. weak norms
For the sake of concreteness denote by $M_0(X)$ the linear space of all signed Borel measures $\sigma$ with $\sigma(X)=0$ on some metric space $(X,d)$ and fix some base point $x_0\in X$. On this space …
25
votes
6
answers
10k
views
Metrization of weak convergence of signed measures
Edit: Changed from "Hausdorff" to "metric" spaces.
Let $\mathcal{M}(\Omega)$ denote the space of signed regular Borel measures on a compact metric space $\Omega$. By Riesz-Markov, this is the dual spa …
1
vote
Reference request: regularity of functionals on the space of probability measures
One thing that is straightforward would be to extend $F$ to the full space $\mathcal{M}$ of signed measures by setting $F(\mu) = -\infty$ if $\mu$ is not a probability measure. This extension would pr …
1
vote
Norms for complex measures
You may look at the Kantorovich-Rubinstein norm mentioned in this answer. It also goes under the name "flat norm" but I don't know a reference for this. Standard references for these things are the "M …
4
votes
Accepted
Coupling of non-probability/sub-probability measures
I thought, I could turn the comments into an answer…
The approach by couplings does not work without modifications and the reason is that couplings do not exist if the measures have different total m …