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I quote Kuo (2006):

Let $C$ be the Banach space of real-valued continuous functions $\omega$ on $[0,1]$ with $\omega(0)=0$.
A cylindrical subset $A$ of $C$ is a set of the form $$A=\{\omega\in C: (\omega(t_1),\omega(t_2),\ldots,\omega(t_n))\in U\}\tag{1}$$ where $0<t_1<t_2<\ldots<t_n\leq 1$ and $U\in\mathcal{B}(\mathbb{R}^n)$, the Borel $\sigma$-field.
Let $\mathcal{R}$ be the collection of all cylindrical subsets of $C$. Obviously, $\mathcal{R}$ is a field. However, it is not a $\sigma$-field.
Suppose $A\in\mathcal{R}$ is given by $(1)$. Define $\mu(A)$ by $$\mu(A)=\displaystyle{\int_U \prod_{i=1}^n}\bigg(\frac{1}{\sqrt{2\pi(t_i-t_{i-1})}}\exp\bigg[-\frac{(u_i-u_{i-1})^2}{2(t_i-t_{i-1}))}\bigg]\bigg)du_1\ldots du_n\tag{2}$$ where $t_0=u_0=0$
[...] Now, consider the probability measure on $\mathbb{R}^n$ to be defined as if follows: $$\mu_{t_1,t_2,\ldots,t_n}(U)=\displaystyle{\int_{\mathbb{R}}\int_{U}\ \prod_{i=1}^n}\bigg(\frac{1}{\sqrt{2\pi(t_i-t_{i-1})}}\exp\bigg[-\frac{(u_i-u_{i-1})^2}{2(t_i-t_{i-1}))}\bigg]\bigg)du_1\ldots du_n d\nu(u_0)\tag{3}$$ where $U\in\mathcal{B}(\mathbb{R}^n)$, $\nu$ is a probability measure on $\mathbb{R}$ and we use the following convention for the integrand: $$\displaystyle{\frac{1}{\sqrt{2\pi t_i}}}e^-{\displaystyle{\frac{(u_1-u_{0})}{2t_1}}du_1}\bigg\vert_{t_1=0}=d\delta_{u_0}(u_1)\tag{4}$$ where $\delta_{u_0}$ is the Dirac delta measure at $u_0$.

Observe that the integral in the right-hand side of $(3)$ with $\nu=\delta_0$ is exactly the same as the one in the right-hand side of equation $(2)$ for the Wiener measure $\mu$.
[...] Consider now the stochastic process $$Y(t,\omega)=\omega(t),\text{ }\omega\in\mathbb{R}^{[0,\infty)}$$ If we set $n=1$ and $t_1=0$, by $(3)$ and $(4)$, we have that: $$\mathbb{P}\{Y(0)\in U\}=\displaystyle{\int_{\mathbb{R}}\int_{U}\frac{1}{\sqrt{2\pi t_i}}}e^-{\displaystyle{\frac{(u_1-u_{0})}{2t_1}}du_1}\bigg\vert_{t_1=0}d\nu(u_0)\tag{5}$$ $$\begin{split}=\displaystyle{\int_{\mathbb{R}}\bigg(\displaystyle{\int_U}d\delta_{u_0}(u_1)\bigg)d\nu(u_0)}\end{split}$$ $$\begin{split}=\displaystyle{\int_{\mathbb{R}}\delta_{u_0}(U)d\nu(u_0)}\end{split}$$ $$\begin{split}=\nu(U)\text{, }U\in\mathcal{B}(\mathbb{R})\end{split}$$

Some doubts:

  1. Does $(4)$ mean that the "quantity" $\displaystyle{\frac{1}{\sqrt{2\pi t_i}}}e^-{\displaystyle{\frac{(u_1-u_{0})}{2t_1}}du_1}\bigg\vert_{t_1=0}$, evaluated at $t_1=0$, equals $d\delta_{u_0}(u_1)$?;
  2. Does it hold true that $\delta_{u_0}=\delta_0=1$ by definition?
  3. Why "the integral in the right-hand side of $(3)$ with $\nu=\delta_0$ is exactly the same as the one in the right-hand side of equation $(2)$ for the Wiener measure $\mu$"?
  4. Why, in the last equality of $(5)$, $\int_{\mathbb{R}}\delta_{u_0}(U)d\nu(u_0)=\nu(U)\text{, }U\in\mathcal{B}(\mathbb{R})$ and NOT $\int_{\mathbb{R}}\delta_{u_0}(U)d\nu(u_0)=\delta_{u_0}(U)\cdot\nu(\mathbb{R})$?

1 Answers1

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I will use the notation $\nu(\mathrm d u)$ instead of the confusing notation $\mathrm d\nu(u)$ as explained in my answer here

  1. (4) is more rigorously the limit when $t_1\to 0$ in the sense of measures (or in the sense of distributions).
  2. No, $\delta_c$ is the Dirac delta centered at $c$, which is different from the function $1$. One has $\delta_{u_0} = \delta_0$ if and only if $u_0=0$. However, what is true is $∫ \delta_0 = ∫ \delta_{u_0} = 1$.
  3. Because by the definition of $\delta_0$ as a distribution, if $\nu = \delta_0$ for any continuous function $\varphi$, $$ ∫_{\mathbb R}\varphi(u_0)\,\nu(\mathrm{d} u_0) = \varphi(0) $$ and now if you take $\varphi(u_0)$ as the integral in $(2)$, since it is written that $t_0=u_0=0$, $(2)$ is nothing but $\varphi(0)$.
  4. $u_0$ is the integrated variable in $(5)$, so in any case it cannot be in the final result! First remark that by definition of $\delta_{u_0}$ as a measure, one has $\delta_{u_0}(U) = \mathbf{1}_{U}(u_0)$ (i.e. $\delta_{u_0}(U) = 1$ if $u_0∈ U$, and $0$ if $u_0∉ U$). Therefore $$ \int_{\mathbb R} \delta_{u_0}(U)\,\nu(\mathrm d u_0) = \int_{\mathbb R} \mathbf{1}_{U}(u_0)\,\nu(\mathrm d u_0) = \int_{U} \,\nu(\mathrm d u_0) = \nu(U) $$
LL 3.14
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  • First of all, thank you a lot! As to the points: 1. What do you mean by "in the sense of measures"? 3. Did you mean "if $d\nu=d\delta_0$" and not "if $d\nu=\delta_0$"? Then, could I rewrite the integral as $$\int_{\mathbb{R}}\varphi(u_0)d\nu(u_0)=\int_{\mathbb{R}}\varphi(u_0)d\delta_0(u_0)=\int_{\mathbb{R}}\varphi(u_0)\delta_0d(u_0)=\varphi(0)$$? Are such passages correct? @LL3.14 – Strictly_increasing Oct 05 '20 at 11:10
  • Another fact as to point 3.: if I am not mistaken, according to your reasoning, we have that $$\varphi(u_0)\underbrace{=}{\text{we fix this}}(2)\underbrace{=}{\text{by }u_0=0}\varphi(u_0=0)=\varphi(0)$$ right? @LL3.14 – Strictly_increasing Oct 05 '20 at 12:44
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    Oh, this is just a question of notation. I personally do not like the confusing notation $\mathrm{d}\mu(x)$ for a measure, I prefer $\mu(\mathrm d x)$. See for example my answer here https://math.stackexchange.com/questions/3801916/working-with-infinitesimals-of-the-form-dfx-for-example-dax-and-relating/3807217#3807217. I modified my answer and wrote $\nu(\mathrm d x)$ instead of $\mathrm d\nu(x)$ to be more coherent. – LL 3.14 Oct 05 '20 at 17:09
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    In any case $\mathrm{d}$ and $\delta_0$ are not numbers! I do not know what do you mean with $d\delta_0 = \delta_0 d$? You can write $$ ∫\varphi(u_0),\nu(\mathrm{d}u_0) = ∫\varphi(u_0),\delta_0(\mathrm{d}u_0) = \varphi(0) $$ Yes, $\varphi(u_0) = \varphi(0)$ since $u_0=0$. – LL 3.14 Oct 05 '20 at 17:11
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    Or if you prefer a more condensed notation, you can just write $\langle \mu,\varphi\rangle = ∫ \varphi(x)\mu(\mathrm d x)$ and then $$ \langle \nu,\varphi\rangle = \langle \delta_0,\varphi\rangle = \varphi(0) $$ – LL 3.14 Oct 05 '20 at 17:14
  • Just one last fact: what do you mean by "in the sense of measures" in the answer to point 1.? Anyway, thank you very very much for your precious help!!!! @LL3.14 – Strictly_increasing Oct 05 '20 at 18:35
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    Usually I would define the set of bounded radon measures as the dual of the set of continuous functions vanishing at infinity. Then there is a natural weak convergence by requiring the convergence when multiplying by any continuous function and integrating. But there are several notions of convergence for measures. One can also ask the convergence of the measure of all sets. See e.g. https://en.m.wikipedia.org/wiki/Convergence_of_measures. Several of them will work here, such as weak convergence, Wasserstein distance, ... (but not one of the strongest, the total variation, analogue of $L^1$) – LL 3.14 Oct 05 '20 at 19:18