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Theory and applications of probability and stochastic processes: e.g. central limit theorems, large deviations, stochastic differential equations, models from statistical mechanics, queuing theory.

1 vote
0 answers
67 views

Can any point process be thinned into a homogenous Poisson point process?

Let $X$ be a stationary and isotropic point process. Under what sufficient conditions can $X$ be thinned into an (approximation of an) homogenous Poisson point process $Y$ of positive intensity? What …
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3 votes

positive Harris recurrent, aperiodic, stationary Markov chain

In the following, all results are referenced from Bradley (2005). Suppose that $X := (X_k, k \in \mathbb{Z})$ is a strictly stationary Markov chain. If $X$ is Harris recurrent and aperiodic then $X$ …
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  • 290
0 votes
Accepted

Sum of a random number of identically distributed but dependent random variables?

I [think I have] proved the calculation for $\mu_Q$ and $\sigma^2_Q$ by applying the methods I used in a related problem. I then [also think I have] proved that $Q$ is asymptotically normal (under ce …
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6 votes
1 answer
845 views

Publishing an elementary proof of a less-general and less-useful version of a classic result?

Background Let $X_t$ be a stochastic process on the state space {Working, Broken}. Let $U$ be the cumulative sojourn Working during an interval $[0,\tau]$ (the process's uptime). It is well-known [1 …
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3 votes

Gaussian expectation of an exponentiated outer product

The following solves the algebra for element-wise calculations by brute-force, and extracts a 'matrix-form solution' of sorts. For $i = j$ We seek $$ E\left[ \exp\left( X_i^2 \right) \right] = \frac …
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0 votes

Gaussian expectation of an exponentiated outer product

If a 'closed form' solution is allowed to be an infinite series then ... Let $X_i$ be the random variable for the i-th row of $\mathbf{x}$ where $$ X_i \sim N\left( \mu_i, \Sigma_i \right) $$ We se …
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5 votes
1 answer
2k views

Sum of a random number of identically distributed but dependent random variables?

Background Let $X_t$ be the continuous time Markov process on the state space {Working, Broken} with failure rate $\alpha$ and repair rate $\beta$. By elementary calculations [1] $$ \begin{align*} …
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