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1 vote
0 answers
69 views

Stochastic Simulation - Simulation from the Marginal Distributions

I am reviewing some material on MCMC / simulation and I realised I never quite understood this point. Given a joint distribution $f(x_1, ..., x_n) = f(x_1) f(x_2 | x_1)...f(x_n | x_{n-1}, ..., x_1)$ ...
4 votes
1 answer
442 views

Popular mistakes in probability

Question: What not-trivial mistakes do students often make when solving problems in probability theory, mathematical statistics and random processes? Some examples of wrong solutions: Problem 1: Find ...
1 vote
0 answers
43 views

Optimal matching of Bernoulli random variables

Let $Z_1$, ..., $Z_n$ be a sequence of independent Bernoulli random variables such that for all $i\in\left\{1,..,n\right\}$ $Z_i\sim\mathcal{B}(p_i)$ where $p_i < 1/2$. Define $l(x_{1:n}, y_{1:n}) =...
0 votes
1 answer
101 views

Conditional expectation with random variables from different Probability spaces [closed]

Let $(X,\mathcal{F}_X,\mathbb{P})$ and $(Y,\mathcal{F}_Y,\mathbb{Q})$ be two probability spaces. I know that the expectation of random variable $Z:X\rightarrow \mathbb{R}$ is affected by the random ...
1 vote
0 answers
44 views

Renewal reward process's reward tail probability

Suppose we are given a dice with $K$ faces, denoted by $k=1,\dots,K$, where the probability of realizing a face $k$ is $p_k\in[0,1]$ with $\sum_{k=1,\dots,K}p_k=1$. Now, we roll the dice repetitively. ...
1 vote
1 answer
106 views

Probability that a probability will be less than a certain value

Suppose I have a nonnegative random variable $X$ and I don't know its expected value, but I know that its expected value is less than or equal to $a$ with at least probability $p^*$. i.e, $\mathbb{P}(\...
0 votes
1 answer
34 views

Markov Chain Detailed Balance $\pi(x)*P(x, y) = \pi(y)*P(y, x)$

Let's say I have a Markov chain and it has a transition matrix denoted as $P$. The $(row, column)$ elements of the $P$ matrix are denoted as $P(i, j)$. Just by looking at the transition matrix $P$, ...
0 votes
2 answers
46 views

Probability 2 earthquakes happen in a period of time.

The amount of earthquakes that happen at island X follows the Poisson process with mean 2 . Given that 2 earthquakes have happened in this year, find the probability both the earthquakes happen ...
1 vote
1 answer
13 views

Expectation of the process adapted to the filtration of the Wiener process

Suppose $\sigma_t$ is a stochastic process adapted to the filtration $\mathcal{F}_t$ generated by the Wiener process $W_t$. I would like to know how to compute the following expectation: $$E = \mathbb{...
2 votes
0 answers
35 views

Difference between compensator of point process under real parameter an its MLE estimator

Suppose we have some point process $N=N_{\theta_0}$ on the real line, driven by a conditional intensity $\lambda_{\theta_0}$ dependent on some finite-dimensional parameter $\theta_0\in\Theta\subset\...
2 votes
1 answer
56 views

Convergence of weighted sum to Brownian Motion

Let $\{\varepsilon_t\}_{t = 1}^T$ be a sequence of iid random variables such that $\varepsilon_t \sim N(0, \sigma^2)$ and $\sigma^2 > 0$. Then it is known that (see 17.3.6 in James Hamilton's Time ...
3 votes
1 answer
965 views

Two independent Poisson processes.

I am trying to prove the result that exactly $k$ occurrences of a Poisson process before the first occurrence of another independent Poisson process is a geometric random variable. \begin{align} &...
0 votes
1 answer
2k views

What is the probability of getting the same side n times in a row in a coin toss

Assuming everything is fair what are the odds that one of the two sides in a coin toss wins 6 times in a row within the first 6 tosses? Please also answer for the general case ...
1 vote
0 answers
97 views

Unbiased Cumulant Estimate - Fifth Cumulant

I am searching the definition of the $5^{th}$ unbiased cumulant estimate. Let $K_j$, be the $j$-th unbiased cumulant estimate of a probability distribution, based on the sample moments. Let $m_j$ be ...
0 votes
1 answer
39 views

Sub-Gaussian $X_t$, prove $\mathbb{E}\left[\sup_{t\in T}X_t \right] \leq 2 \mathbb{E}\left[\sup_{\rho(t,s)\leq \delta}(X_t-X_s) \right]+J(\delta,T)$

This is a question-and-answer just for me, but if you have alternate answers or comments, feel free to share them. Let $(T,\rho)$ be a metric space and $\{X_t\}_{t\in T}$ be a sub-Gaussian process ...
0 votes
1 answer
49 views

A Gaussian process and a Rademacher proecss are sub-Gaussian

This is a question-and-answer just for me, but if you have alternate answers or comments, feel free to share them. Let $(T,\rho)$ be a metric space and $\{X_t\}_{t\in T}$ be a stochastic process ...
4 votes
0 answers
54 views

When $X_t$ is conditionally normal distributed and has density $p_t$, how can we compute $\text E\left[\left\|\nabla\ln p_t(X_t)\right\|^2\right]$?

Let $d\in\mathbb N$ and $(X_t)_{t\ge0}$ be an $\mathbb R^d$-valued process. Assume $$\operatorname P\left[X_t\in\;\cdot\;\mid X_0\right]=\mathcal N(X_0,\Sigma_t)\tag1$$ for some covariance matrix $\...
5 votes
2 answers
130 views

Ergodic series converge to the expectation?

Let $(X_i, Y_i)_{i\in\mathbb{N}}$ be a real-valued stochastic process. We say that $X$ is mean-ergodic, if $$\frac{1}{n}\sum_{i=1}^nX_i\to \mathbb{E}X_1$$ in probability as $n\to\infty$. Let $S_n:=\{i\...
2 votes
1 answer
104 views

Asymptotic Gambler's Ruin Probability with Unequal Gain/Loss with Zero-Mean Payoff Distribution

The gambler's ruin problem with unequal gain/loss with a payoff distribution whose support is a finite subset of $\mathbb Z$ is an old problem; for example, see Feller (1968, Vol.1, Section XIV.8) and ...
1 vote
1 answer
117 views

How to deduce an expression of a specific conditional expression

The problem occurs when reading Bombardini et al., 2023, "Did US Politicians Expect the China Shock?", American Economic Review, Vol.1, PP174-209. The authors define $\xi_{it}$ to be a ...
2 votes
1 answer
119 views

Covariance Operator corresponding to multivariate covariance function

The usual definition of a covariance operator on $L_2(D)$ is: $$ C : L_2(D) \to L_2(D), \qquad (C \psi)(x) = \int_D c(x,y) \psi(y) dy \qquad \forall x\in D, ~~\psi \in L_2(D), $$ where $c(x,y): D \...
1 vote
0 answers
14 views

M/M/1 Queues : Exclusive Queue Length is not Markov

For a M/M/1 queue let $N_q(t) = (Q(t)-1)^{+}$ be the number of customers in the queue except the one being served. We have to show that $N_q(t)$ is not a continuous-time Markov chain. [src: Sidney ...
0 votes
1 answer
28 views

Variance of time integral of a function on an Ito process

I was struggling a bit with the time integral of an Ito process. Say I have this: $$\int^T_t \alpha\circ X_t ds$$ Where $X_t$ is an Ito process, and $\alpha$ is a continuous function. What can we say ...
0 votes
1 answer
56 views

Can addition of noise to dynamical system reduce estimation errors

I am using Kalman filter to estimate the states of a stochastic dynamical system which has very very small noise( consider zero ). The filter is not aware that the noise is zero. Implementation of KF ...
0 votes
0 answers
64 views

How to find joint pdf

The random arrival of $k$ phone calls within a time interval of length $t$ is described by the following pdf $$f(t) = \frac{\lambda^k}{(k-1)!} t^{k-1} e^{-\lambda t}$$ where parameter $\lambda$ ...
0 votes
1 answer
43 views

Question on determining the posterior pdf

Can someone tell me how the pdf of noise (w) is equivalent to the conditional pdf of observations (x) given A, assuming noise is independent of A for the equation x[n]=A+w[n] where A is the mean (and ...
0 votes
0 answers
28 views

Genomic and sum of geometric random variables

In their paper The Maximum of independent Geometric Random Variables as the Time for Genomic Evolutionthe authors noted that if to consider the genomic word of L letters, than the measure of the time ...
1 vote
0 answers
47 views

Mean value of sqrt. root cox-ingersoll-ross process

Consider the so-called Cox-Ingersoll-Process model \begin{equation} dr_t=a(b-r_t)dt+\sigma \sqrt{r_t}dW_t \end{equation} It can be shown (Wikipedia), that the mean of this process is \begin{...
2 votes
1 answer
99 views

Variance recursion formula in Galton-Watson process

Consider a Galton-Watson process with expected offspring $\mathbb{E}[\xi]=\mu<\infty$ and variance $\text{Var}(\xi)=\sigma^2<\infty$ where the offspring in generation $t\in\mathbb{N}$ is given ...
3 votes
1 answer
94 views

Existence of Malthusian parameter

Consider a continuous time point process $\eta(t)$ representing the number of points in the interval $[0, t]$. Let $\eta(\infty)$ be distributed as the total number of children of a particle. Define $\...

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