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We establish a lower bound on the entropy of weighted sums of (possibly dependent) random variables $(X_1, X_2, \dots, X_n)$ possessing a symmetric joint distribution. Our lower bound is in terms of the joint entropy of $(X_1, X_2, \dots,…

Information Theory · Computer Science 2018-01-16 Jing Hao , Varun Jog

We consider a Bayesian problem of estimating of probability of success in a series of conditionally independent trials with binary outcomes. We study the asymptotic behaviour of differential entropy for posterior probability density…

Information Theory · Computer Science 2015-07-30 Mark Kelbert , Pavel Mozgunov

Several proofs of the monotonicity of the non-Gaussianness (divergence with respect to a Gaussian random variable with identical second order statistics) of the sum of n independent and identically distributed (i.i.d.) random variables were…

Information Theory · Computer Science 2007-07-13 Jacob Binia

We establish several Schur-convexity type results under fixed variance for weighted sums of independent gamma random variables and obtain nonasymptotic bounds on their R\'enyi entropies. In particular, this pertains to the recent results by…

Probability · Mathematics 2025-01-28 Giorgos Chasapis , Salil Singh , Tomasz Tkocz

A symmetric random variable is called a Gaussian mixture if it has the same distribution as the product of two independent random variables, one being positive and the other a standard Gaussian random variable. Examples of Gaussian mixtures…

Probability · Mathematics 2019-04-18 Alexandros Eskenazis , Piotr Nayar , Tomasz Tkocz

This paper focuses on inhomogeneous quadratic tests, which involve the sum of a dependent non-central chi-square with a Gaussian random variable. Unfortunately, no closed-form expression is available for the statistical distribution of the…

Applications · Statistics 2018-10-12 Daniel Egea-Roca , Gonzalo Seco-Granados , José A. López-Salcedo

We show that for log-concave real random variables with fixed variance the Shannon differential entropy is minimized for an exponential random variable. We apply this result to derive upper bounds on capacities of additive noise channels…

Probability · Mathematics 2024-03-19 James Melbourne , Piotr Nayar , Cyril Roberto

The family of q-Gaussian and q-exponential probability densities fit the statistical behavior of diverse complex self-similar non-equilibrium systems. These distributions, independently of the underlying dynamics, can rigorously be obtained…

Statistical Mechanics · Physics 2015-05-19 Adrian A. Budini

A Gaussian variational approximation is often used to study interfaces in random media. By considering the 1+1 dimensional directed polymer in a random medium, it is shown here that the variational Ansatz typically leads to a negative…

Disordered Systems and Neural Networks · Physics 2009-10-30 D. B. Saakian , Th. M. Nieuwenhuizen

Differential entropy and log determinant of the covariance matrix of a multivariate Gaussian distribution have many applications in coding, communications, signal processing and statistical inference. In this paper we consider in the high…

Statistics Theory · Mathematics 2015-03-10 T. Tony Cai , Tengyuan Liang , Harrison H. Zhou

A strengthened version of the central limit theorem for discrete random variables is established, relying only on information-theoretic tools and elementary arguments. It is shown that the relative entropy between the standardised sum of…

Probability · Mathematics 2021-06-02 Lampros Gavalakis , Ioannis Kontoyiannis

Gaussian distribution of a quantum state with continuous spectrum is known to maximize the Shannon entropy at a fixed variance. Applying it to a pair of canonically conjugate quantum observables $\hat x$ and $\hat p$, quantum entropic…

Quantum Physics · Physics 2015-07-21 Wonmin Son

We derive a scale-free bound on the density of the maximum of a centered Gaussian vector. The basic bound is non-uniform, depends logarithmically on the dimension, and allows any covariance matrix. When the largest marginal variance is…

Statistics Theory · Mathematics 2026-05-29 Suhas Vijaykumar

This paper re-examines the density for sums of independent exponential, Erlang and gamma random variables. By using a divided difference perspective, the paper provides a unified approach to finding closed-form formulae for such…

Probability · Mathematics 2021-08-10 Edmond Levy

A simple multivariate version of Costa's entropy power inequality is proved. In particular, it is shown that if independent white Gaussian noise is added to an arbitrary multivariate signal, the entropy power of the resulting random…

Information Theory · Computer Science 2008-04-30 M. Payaró , D. P. Palomar

From a suitable integral representation of the Laplace transform of a positive semi-definite quadratic form of independent real random variables with not necessarily identical densities a univariate integral representation is derived for…

Statistics Theory · Mathematics 2007-11-01 T. Royen

For an ergodic Brownian diffusion with invariant measure $\nu$, we consider a sequence of empirical distributions ($\nu$n) n$\ge$1 associated with an approximation scheme with decreasing time step ($\gamma$n) n$\ge$1 along an adapted…

Probability · Mathematics 2018-10-09 I Honoré

In this paper we consider a weighted version of one dimensional discrete Hardy's Inequality on half-line with power weights of the form $n^\alpha$. Namely we consider: \begin{equation} \sum_{n=1}^\infty |u(n)-u(n-1)|^2 n^\alpha \geq…

Functional Analysis · Mathematics 2022-05-20 Shubham Gupta

Exact formulas are derived for the probability density functions of the sum and difference of two independent non-central gamma distributed random variables, with both series and integral representations of the density presented. These…

Probability · Mathematics 2026-05-18 Robert E. Gaunt , Heather L. Sutcliffe

Entropy comparison inequalities are obtained for the differential entropy $h(X+Y)$ of the sum of two independent random vectors $X,Y$, when one is replaced by a Gaussian. For identically distributed random vectors $X,Y$, these are closely…

Information Theory · Computer Science 2024-07-24 Lampros Gavalakis , Ioannis Kontoyiannis , Mokshay Madiman
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