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Let $\{X_\alpha\}$ be a family of random variables satisfying some distribution with a parameter $\alpha$, $E(X_{\alpha})$ be the expectation, and $Var(X_{\alpha})$ be the variance. In this paper, we study the infimum values of three…

Probability · Mathematics 2026-02-09 Rong-Sheng Hu , Ze-Chun Hu , Zhen Huang , Mu-Xuan Li

The Poisson distribution of order $k$ is a special case of a compound Poisson distribution. For $k=1$ it is the standard Poisson distribution. Although its probability mass function (pmf) is known, what is lacking is a $visual$…

Probability · Mathematics 2023-09-26 S. R. Mane

The variable-length source coding problem allowing the error probability up to some constant is considered for general sources. In this problem the optimum mean codeword length of variable-length codes has already been determined. On the…

Information Theory · Computer Science 2018-10-19 Ryo Nomura , Hideki Yagi

An index of uniformity is developed as an alternative to the maximum-entropy principle for selecting continuous, differentiable probability distributions $\mathcal{P}$ subject to constraints $C$. The uniformity index developed in this paper…

Methodology · Statistics 2016-06-02 Michael E. Beyer

Let $L_n(k)$ denote the least common multiple of $k$ independent random integers uniformly chosen in $\{1,2,\ldots ,n\}$. In this note, using a purely probabilistic approach, we derive a criterion for the convergence in distribution as…

Probability · Mathematics 2019-11-11 Alin Bostan , Alexander Marynych , Kilian Raschel

A user generates n independent and identically distributed data random variables with a probability mass function that must be guarded from a querier. The querier must recover, with a prescribed accuracy, a given function of the data from…

Information Theory · Computer Science 2022-01-03 Ajaykrishnan Nageswaran , Prakash Narayan

The probabilistic degree of a Boolean function $f:\{0,1\}^n\rightarrow \{0,1\}$ is defined to be the smallest $d$ such that there is a random polynomial $\mathbf{P}$ of degree at most $d$ that agrees with $f$ at each point with high…

Computational Complexity · Computer Science 2019-10-08 Srikanth Srinivasan , Utkarsh Tripathi , S. Venkitesh

In this work, we continue the line of research on the complexity of distributions (Viola, Journal of Computing 2012), and study samplers defined by low degree polynomials. An $n$-tuple $P = (P_1,\dots, P_n)$ of functions $P_i \colon…

Computational Complexity · Computer Science 2026-05-05 Mohammad Mahdi Khodabandeh , Igor Shinkar

In this paper we consider the normalized lengths of the factors of some factorizations of random words. First, for the \emph{Lyndon factorization} of finite random words with $n$ independent letters drawn from a finite or infinite totally…

Probability · Mathematics 2021-11-05 Elahe Zohoorian Azad , Philippe Chassaing

A parametric method similar to autoregressive spectral estimators is proposed to determine the probability density function (pdf) of a random set. The method proceeds by maximizing the likelihood of the pdf, yielding estimates that perform…

Data Analysis, Statistics and Probability · Physics 2009-10-31 T. Dudok de Wit , E. Floriani

Kostadinova and Minkova published an expression for the probability mass function (pmf) of the Poisson distribution of order $k$, as a combinatorial sum ($\mathit{Pliska~Stud.~Math.~Bulgar.}\ {\bf 22},\ 117-128\ (2013)$). Inspired by their…

Probability · Mathematics 2023-10-16 S. R. Mane

We consider the lossless compression bound of any individual data sequence. If we fit the data by a parametric model, the entropy quantity $nH({\hat \theta}_n)$ obtained by plugging in the maximum likelihood estimate is an underestimate of…

Information Theory · Computer Science 2024-01-23 Lei M Li

If two probability density functions (PDFs) have values for their first $n$ moments which are quite close to each other (upper bounds of their differences are known), can it be expected that the PDFs themselves are very similar? Shown below…

Statistics Theory · Mathematics 2018-08-16 Pranava Chaitanya Jayanti , Konstantina Trivisa

We define the min-min expectation selection problem (resp. max-min expectation selection problem) to be that of selecting k out of n given discrete probability distributions, to minimize (resp. maximize) the expectation of the minimum value…

Data Structures and Algorithms · Computer Science 2007-05-23 David Eppstein , George Lueker

We provide upper and lower bounds for the expected length $\mathbb E(L_{n,m})$ of the longest common pattern contained in $m$ random permutations of length $n$. We also address the tightness of the concentration of $L_{n,m}$ around $\mathbb…

Combinatorics · Mathematics 2014-02-04 Michael Earnest , Anant Godbole , Yevgeniy Rudoy

The maximum product of spacings (MPS) is employed in the estimation of the Generalized Extreme Value Distribution (GEV) and the Generalized Pareto Distribution (GPD). Efficient estimators are obtained by the MPS for all $\gamma$. This…

Statistics Theory · Mathematics 2007-06-13 T. S. T. Wong , W. K. Li

We study the probabilistic degree over reals of the OR function on $n$ variables. For an error parameter $\epsilon$ in (0,1/3), the $\epsilon$-error probabilistic degree of any Boolean function $f$ over reals is the smallest non-negative…

Computational Complexity · Computer Science 2022-11-24 Siddharth Bhandari , Prahladh Harsha , Tulasimohan Molli , Srikanth Srinivasan

We investigate the variance of the length of the longest common subsequences of two independent random words of size $n$, where the letters of one word are i.i.d. uniformly drawn from $\{\alpha_1, \alpha_2, \cdots, \alpha_m\}$, while the…

Probability · Mathematics 2018-12-27 Christian Houdré , Qingqing Liu

Let $P = \{p(i)\}$ be a measure of strictly positive probabilities on the set of nonnegative integers. Although the countable number of inputs prevents usage of the Huffman algorithm, there are nontrivial $P$ for which known methods find a…

Information Theory · Computer Science 2007-07-13 Michael B. Baer

Let us assume that $f$ is a continuous function defined on the unit ball of $\mathbb R^d$, of the form $f(x) = g (A x)$, where $A$ is a $k \times d$ matrix and $g$ is a function of $k$ variables for $k \ll d$. We are given a budget $m \in…

Numerical Analysis · Mathematics 2012-01-18 Massimo Fornasier , Karin Schnass , Jan Vybiral