Stéphane Laurent
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 Mar15 comment Notation $\mathrm{mod}$ in ergodic theory $B=A \mod \mu$ $\iff$ $\mu(B \Delta A)=0$ $\iff$ ${\boldsymbol 1}_B={\boldsymbol 1}_A \quad \mu \text{ a.e.}$. Mar7 answered Kolmogorov distance between univariate gaussians Feb14 asked nice stationary process with discrete spectrum Feb13 answered Must any set of positive Lebesgue measure contain a bounded set of positive measure? Feb5 comment Computing confidence bounds on entropy given an empirical sample from a multinomial distribution? The posterior distribution of $(p_1, \ldots, p_d)$ is a Dirichlet distribution. But I don't know what is the function $f$. Feb4 comment Computing confidence bounds on entropy given an empirical sample from a multinomial distribution? Hello, using a Bayesian approach you can easily get a credibility interval for any function $f(p_1, \ldots, p_d)$. Using the Jeffreys posterior distribution, you can expect that the $95\%$-credibility interval provides a $\approx 95\%$-confidence interval. Nov12 answered Product of ergodic transformations Nov9 comment Disintegration-like theorem @Ilya Actually you can drop the probabilistic objects (the random variables), the measure $\mu$ in Michael's answer plays the role of the law of $(A_1,A_2,B_2)$ (but I don't know why his answer looks so complicated). I prefer the probabilistic framework because of the interpretation of the integrals. Nov9 answered Disintegration-like theorem Sep27 comment counting combinations of {+1, -1} with constraints Nice question but it should be better for math.stackexchange Aug21 revised Independence of Filtration minor corrections Aug21 suggested approved edit on Independence of Filtration Aug21 answered Markov property with respect to a filtration Aug19 awarded Yearling Jul2 awarded Curious Jun30 awarded Revival Jun30 revised Definition of entropy of an ergodic measure added 1 character in body Jan30 comment Different definitions of an ergodic stationary process By "wide-sense stationary" you mean stationary correlation ? Jan29 comment What am I doing wrong in calculating Fisher Information of Triangular Distribution? $x$ is a random variable and you have not calculated the expectation in your last step Jan29 comment Ergodic Process: Does it visit all state? @triomphe Actually this should be equivalent for a discrete-time stationary process. Are you interested in discrete or continuous time ?