List questions from probability-limit-theorems

155

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Determining norming and centering constants to guarantee weak convergence to a non-degenerate distribution

Published on 22 Apr 2020 - 5:58

303

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Bounded probability implies convergence in probability

Published on 24 Apr 2020 - 15:01

189

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Conditions for a.s convergence of a gamma series

Published on 26 Apr 2020 - 14:46

147

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Concentration of norm of linearly transformed normal random vector as dimension go to infinity

Published on 26 Mar 2026 - 17:32

266

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A sufficient condition for almost sure convergence.

Published on 25 Mar 2026 - 15:38

152

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What are sufficient conditions such that consistency of ML estimate implies consistency of MAP estimate?

Published on 11 May 2020 - 16:57

86

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Understanding stochastic Big-$O$ notation in a stochastic process context

Published on 15 May 2020 - 11:49

295

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Show that maximum of iid. random variables converge in mean

Published on 16 May 2020 - 20:41

122

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Limit of Binomial CDF

Published on 17 May 2020 - 18:50

119

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Applying de Moivre-Laplace Theorem correctly

Published on 18 May 2020 - 15:51

243

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convergence a.s. and in probability of discrete random variable

Published on 25 Mar 2026 - 15:46

227

Views

Applying the Central Limit Theorem to show $\lim_{N \rightarrow \infty} \mathbb{P}(0 \leq \sqrt{12N}(\overline{X}_n -\frac{1}{2}) \leq 1) = I$

Published on 20 May 2020 - 11:31

32

Views

Is this limiting total variation result valid?

Published on 20 May 2020 - 14:29

67

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An application of Lebesgue's Dominated Convergence Theorem. Is that correct?

Published on 21 May 2020 - 11:14

79

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Sum of bernoullis

Published on 21 May 2020 - 11:56

List Question

Determining norming and centering constants to guarantee weak convergence to a non-degenerate distribution

Bounded probability implies convergence in probability

Conditions for a.s convergence of a gamma series

Concentration of norm of linearly transformed normal random vector as dimension go to infinity

A sufficient condition for almost sure convergence.

What are sufficient conditions such that consistency of ML estimate implies consistency of MAP estimate?

Understanding stochastic Big-$O$ notation in a stochastic process context

Show that maximum of iid. random variables converge in mean

Limit of Binomial CDF

Applying de Moivre-Laplace Theorem correctly

convergence a.s. and in probability of discrete random variable

Applying the Central Limit Theorem to show $\lim_{N \rightarrow \infty} \mathbb{P}(0 \leq \sqrt{12N}(\overline{X}_n -\frac{1}{2}) \leq 1) = I$

Is this limiting total variation result valid?

An application of Lebesgue's Dominated Convergence Theorem. Is that correct?

Sum of bernoullis

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