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Using a differential equation approach asymptotic expansions are rigorously obtained for Lommel, Weber, Anger-Weber and Struve functions, as well as Neumann polynomials, each of which is a solution of an inhomogeneous Bessel equation. The…

Classical Analysis and ODEs · Mathematics 2021-04-06 T. M. Dunster

This paper develops tests for inequality constraints of nonparametric regression functions. The test statistics involve a one-sided version of $L_p$-type functionals of kernel estimators $(1 \leq p < \infty)$. Drawing on the approach of…

Statistics Theory · Mathematics 2023-08-28 Sokbae Lee , Kyungchul Song , Yoon-Jae Whang

This paper addresses the topic of robust Bayesian compressed sensing over finite fields. For stationary and ergodic sources, it provides asymptotic (with the size of the vector to estimate) necessary and sufficient conditions on the number…

Information Theory · Computer Science 2014-01-20 Wenjie Li , Francesca Bassi , Michel Kieffer

We have solved a number of holonomic PDEs derived from the Bessel modules which are related to the generating functions of classical Bessel functions and the difference Bessel functions recently discovered by Bohner and Cuchta. This…

Classical Analysis and ODEs · Mathematics 2023-03-29 Yik Man Chiang , Avery Ching , Xiaoli Lin

By means of two simple convexity arguments we are able to develop a general method for proving consistency and asymptotic normality of estimators that are defined by minimisation of convex criterion functions. This method is then applied to…

Statistics Theory · Mathematics 2011-07-20 Nils Lid Hjort , David Pollard

We give an overview of the theory of functional relations for zeta-functions of root systems, and show some new results on functional relations involving zeta-functions of root systems of types $B_r$, $D_r$, $A_3$ and $C_2$. To show those…

Number Theory · Mathematics 2018-11-15 Yasushi Komori , Kohji Matsumoto , Hirofumi Tsumura

The computation and inversion of the binomial and negative binomial cumulative distribution functions play a key role in many applications. In this paper, we explain how methods used for the central beta distribution function (described in…

Classical Analysis and ODEs · Mathematics 2020-01-14 A. Gil , J. Segura , N. M. Temme

Let \{X_1, X_2, ...\} be a sequence of independent and identically distributed positive random variables of Pareto-type with index \alpha>0 and let \{N(t); t\geq 0\} be a counting process independent of the X_i's. For any fixed t\geq 0,…

Probability · Mathematics 2007-06-13 S. A. Ladoucette , J. L. Teugels

We study the asymptotic distribution of roots of Lommel polynomials as polynomials of the order with a variable and purely imaginary argument. The roots are complex and accumulate on certain curves in the complex plane. We prove existence…

Classical Analysis and ODEs · Mathematics 2021-02-02 Petr Blaschke , František Štampach

A compilation of new results on the asymptotic behaviour of the Humbert functions $\Psi_1$ and $\Psi_2$, and also on the Appell function $F_2$, is presented. As a by-product, we confirm a conjectured limit which appeared recently in the…

Classical Analysis and ODEs · Mathematics 2025-09-12 Peng-Cheng Hang , Malte Henkel , Min-Jie Luo

The association between two random variables is often of primary interest in statistical research. In this paper semiparametric models for the association between random vectors X and Y are considered which leave the marginal distributions…

Statistics Theory · Mathematics 2012-04-16 Angelika Franke , Gerhard Osius

This paper is mainly concerned with asymptotic studies of weighted bootstrap for u- and v-statistics. We derive the consistency of the weighted bootstrap u- and v-statistics, based on i.i.d. and non i.i.d. observations, from some more…

Statistics Theory · Mathematics 2012-10-23 Miklos Csorgo , Masoud M. Nasari

The coefficient sequences of multivariate rational functions appear in many areas of combinatorics. Their diagonal coefficient sequences enjoy nice arithmetic and asymptotic properties, and the field of analytic combinatorics in several…

Symbolic Computation · Computer Science 2020-11-19 Stephen Melczer , Bruno Salvy

New asymptotic relations between the $L_p$-errors of best approximation of univariate functions by algebraic polynomials and entire functions of exponential type are obtained for $p\in (0,\iy]$. General asymptotic relations are applied to…

Classical Analysis and ODEs · Mathematics 2022-12-26 Michael I. Ganzburg

We define a measure on tuples of partitions, called the symplectic Schur process, that should be regarded as the right analogue of the Schur process of Okounkov-Reshetikhin for the Cartan type C. The weights of our measure include factors…

Mathematical Physics · Physics 2026-04-30 Cesar Cuenca , Matteo Mucciconi

We establish sufficient conditions for the asymptotic normality of kernel density estimators, applied to causal linear random fields. Our conditions on the coefficients of linear random fields are weaker than known results, although our…

Statistics Theory · Mathematics 2012-01-04 Yizao Wang , Michael Woodroofe

The Bayesian Context Trees (BCT) framework is a recently introduced, general collection of statistical and algorithmic tools for modelling, analysis and inference with discrete-valued time series. The foundation of this development is built…

Information Theory · Computer Science 2023-09-06 Ioannis Kontoyiannis

We obtain the asymptotic variance, as the degree goes to infinity, of the normalized number of real roots of a square Kostlan-Shub-Smale random polynomial system of any size. Our main tools are the Kac-Rice formula for the second factorial…

Probability · Mathematics 2018-05-01 Diego Armentano , Jean-Marc Azaïs , Federico Dalmao , José R. León

The objective of this paper is to establish a general asymptotic representation (\textit{GAR}) for a wide range of statistics, employing two fundamental processes: the functional empirical process (\textit{fep}) and the residual functional…

Statistics Theory · Mathematics 2025-08-08 Gane Samb Lo , Tchilabalo Abozou Kpanzou , Gandasor Bonyiri Onesiphore Da

Approximate Bayesian Computation is a family of likelihood-free inference techniques that are well-suited to models defined in terms of a stochastic generating mechanism. In a nutshell, Approximate Bayesian Computation proceeds by computing…

Computation · Statistics 2010-07-28 Michael Blum