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We describe a very simple method for `consistent sampling' that allows for sampling with replacement. The method extends previous approaches to consistent sampling, which assign a pseudorandom real number to each element, and sample those…

Data Structures and Algorithms · Computer Science 2018-08-31 Ronald L. Rivest

We define Poisson genericity for infinite sequences in any finite or countable alphabet with an invariant exponentially-mixing probability measure. A sequence is Poisson generic if the number of occurrences of blocks of symbols…

In this paper, we study the hypothesis testing problem of, among $n$ random variables, determining $k$ random variables which have different probability distributions from the rest $(n-k)$ random variables. Instead of using separate…

Information Theory · Computer Science 2013-05-28 Weiyu Xu , Lifeng Lai

There have been several efforts to extend distributional semantics beyond individual words, to measure the similarity of word pairs, phrases, and sentences (briefly, tuples; ordered sets of words, contiguous or noncontiguous). One way to…

Machine Learning · Computer Science 2013-10-21 Peter D. Turney

A combinatorial methods are used to investigate some properties of certain generalized Stirling numbers, including explicit formula and recurrence relations. Furthermore, an expression of these numbers with symmetric function is deduced.

Combinatorics · Mathematics 2014-11-25 Hacène Belbachir , Amine Belkhir , Imad Eddine Bousbaa

The Conway-Maxwell-Poisson distribution is a two-parameter generalisation of the Poisson distribution that can be used to model data that is under- or over-dispersed relative to the Poisson distribution. The normalizing constant…

Statistics Theory · Mathematics 2019-04-05 Robert E. Gaunt , Satish Iyengar , Adri B. Olde Daalhuis , Burcin Simsek

Importance sampling (IS) and numerical integration methods are usually employed for approximating moments of complicated target distributions. In its basic procedure, the IS methodology randomly draws samples from a proposal distribution…

Computation · Statistics 2022-04-12 Víctor Elvira , Luca Martino , Pau Closas

In this pedagogical text aimed at those wanting to start thinking about or brush up on probabilistic inference, I review the rules by which probability distribution functions can (and cannot) be combined. I connect these rules to the…

Data Analysis, Statistics and Probability · Physics 2012-05-22 David W. Hogg

Nonprobability (convenience) samples are increasingly sought to stabilize estimations for one or more population variables of interest that are performed using a randomized survey (reference) sample by increasing the effective sample size.…

This paper deals with empirical processes of the type \[C_n(B)=\sqrt{n}\{\mu_n(B)-P(X_{n+1}\in B\mid X_1,...,X_n)\},\] where $(X_n)$ is a sequence of random variables and $\mu_n=(1/n)\sum_{i=1}^n\delta_{X_i}$ the empirical measure.…

Statistics Theory · Mathematics 2010-01-14 Patrizia Berti , Irene Crimaldi , Luca Pratelli , Pietro Rigo

This paper offers a commentary on the use of notions of statistical significance in choice modelling. We review the reasons for uncertainty in parameter estimates, provide a precise discussion on the computation of measures of uncertainty…

Econometrics · Economics 2026-05-18 Stephane Hess , Andrew Daly , Michiel Bliemer , Angelo Guevara , Ricardo Daziano , Thijs Dekker

Let $w$ be a finite word over the alphabet $\{0,1\}$. For any natural number $n$, let $s_w(n)$ denote the number of occurrence of $w$ in the binary expansion of $n$ as a scattered subsequence. We study the behavior of the partial sum…

Number Theory · Mathematics 2024-11-18 Pranjal Jain , Shuo Li

This study focuses on statistical inference for compound models of the form $X=\xi_1+\ldots+\xi_N$, where $N$ is a random variable denoting the count of summands, which are independent and identically distributed (i.i.d.) random variables…

Statistics Theory · Mathematics 2025-07-22 Denis Belomestny , Ekaterina Morozova , Vladimir Panov

Two approximations are frequently used in statistical physics: the first one, which we shall name the mean values approximation, is generally (and improperly) named as "maximum term approximation". The second is the "Stirling…

General Physics · Physics 2007-05-23 Conrado Hoffmann

We consider the sequential composite binary hypothesis testing problem in which one of the hypotheses is governed by a single distribution while the other is governed by a family of distributions whose parameters belong to a known set…

Information Theory · Computer Science 2022-03-30 Jiachun Pan , Yonglong Li , Vincent Y. F. Tan

We use Poisson summation formula to calculate integrals of producs of sinc functions (cf. [4]) and related integrals as in [5] and [3]. We also generalize the one in [5] and introduce other remarkable integrals. Finally we give a sum…

Classical Analysis and ODEs · Mathematics 2014-07-01 Gert Almkvist , Jan Gustavsson

Importance Sampling methods are broadly used to approximate posterior distributions or some of their moments. In its standard approach, samples are drawn from a single proposal distribution and weighted properly. However, since the…

Computation · Statistics 2019-11-05 Víctor Elvira , Luca Martino , David Luengo , Mónica F. Bugallo

Nonprobability (convenience) samples are increasingly sought to reduce the estimation variance for one or more population variables of interest that are estimated using a randomized survey (reference) sample by increasing the effective…

Composite indicators aggregate a set of variables using weights which are understood to reflect the variables' importance in the index. In this paper we propose to measure the importance of a given variable within existing composite…

Applications · Statistics 2018-08-02 Paolo Paruolo , Andrea Saltelli , Michaela Saisana

Two new information-theoretic methods are introduced for establishing Poisson approximation inequalities. First, using only elementary information-theoretic techniques it is shown that, when $S_n=\sum_{i=1}^nX_i$ is the sum of the (possibly…

Probability · Mathematics 2010-10-21 Ioannis Kontoyiannis , Peter Harremoes , Oliver Johnson