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Let T be a unital triangular algebra, let n > 1 be an integer, let gamma be an invertible element of Z(T), the center of T, and let Psi, Omega:\mathcal{T}\rightarrow \mathcal{T}$ be additive mappings satisfying \begin{align*} \Psi(X^n) =…

Rings and Algebras · Mathematics 2025-11-25 Amin Hosseini

Asymptotic behavior (with respect to the number of trials) of symmetric generalizations of binomial distributions and their related entropies are studied through three examples. The first one derives from the q-exponential as a generating…

Statistical Mechanics · Physics 2014-12-02 H. Bergeron , E. M. F. Curado , J. P. Gazeau , Ligia M. C. S. Rodrigues

We herein establish an asymptotic representation theorem for locally asymptotically normal quantum statistical models. This theorem enables us to study the asymptotic efficiency of quantum estimators such as quantum regular estimators and…

Quantum Physics · Physics 2024-11-14 Akio Fujiwara , Koichi Yamagata

A definition of qualitative robustness for point estimators in general statistical models is proposed. Some criteria for robustness are established and applied to estimators in parametric, semiparametric, and nonparametric models. In…

Statistics Theory · Mathematics 2015-06-18 Henryk Zähle

Let $L_1$ and $L_2$ be linear forms of real-valued independent random variables. By Heyde's theorem, if the conditional distribution of $L_2$ given $L_1$ is symmetric, then the random variables are Gaussian. A number of papers are devoted…

Probability · Mathematics 2025-05-20 Gennadiy Feldman

We develop an analogue of probability theory for probabilities taking values in topological groups. We generalize Kolmogorov's method of axiomatization of probability theory: main distinguishing features of frequency probabilities are taken…

Probability · Mathematics 2015-06-26 Andrei Khrennikov

We define susceptibilities as a measure of the response of an observable quantity of a parameterized statistical model to a perturbation of the data for a general class of observables. We define estimators for these susceptibilities as…

Statistics Theory · Mathematics 2026-05-11 Chris Elliott , Daniel Murfet

In this article we study the existence and strong consistency of GEE estimators, when the generalized estimating functions are martingales with random coefficients. Furthermore, we characterize estimating functions which are asymptotically…

Statistics Theory · Mathematics 2017-11-15 Laura Dumitrescu , Ioana Schiopu-Kratina

We consider the marginal models of Liang and Zeger [Biometrika 73 (1986) 13-22] for the analysis of longitudinal data and we develop a theory of statistical inference for such models. We prove the existence, weak consistency and asymptotic…

Statistics Theory · Mathematics 2007-06-13 R. M. Balan , I. Schiopu-Kratina

We study the asymptotical behavior of the $p$-adic singular Fourier integrals $$ J_{\pi_{\alpha},m;\phi}(t) =\bigl< f_{\pi_{\alpha};m}(x)\chi_p(xt), \phi(x)\bigr> =F\big[f_{\pi_{\alpha};m}\phi\big](t), \quad |t|_p \to \infty, \quad t\in…

Mathematical Physics · Physics 2008-08-26 A. Yu. Khrennikov , V. M. Shelkovich

We show that a Gibbs characterization of normalized generalized Gamma processes, recently obtained in Lijoi, Pr\"unster and Walker (2007), can alternatively be derived by exploiting a characterization of exponentially tilted Poisson-Kingman…

Probability · Mathematics 2010-01-02 Annalisa Cerquetti

In this note we extend two characterizations of admissible operators with respect to $\mathrm{L}^p$ to more general Orlicz spaces. The equivalent conditions are given by the property that an associated operator generates a strongly…

Functional Analysis · Mathematics 2022-08-01 René Hosfeld , Birgit Jacob , Felix L. Schwenninger

We provide a comparative study of several widely used off-policy estimators (Empirical Average, Basic Importance Sampling and Normalized Importance Sampling), detailing the different regimes where they are individually suboptimal. We then…

Machine Learning · Statistics 2019-01-30 Thomas Nedelec , Nicolas Le Roux , Vianney Perchet

Bagging is a useful method for large-scale statistical analysis, especially when the computing resources are very limited. We study here the asymptotic properties of bagging estimators for $M$-estimation problems but with massive datasets.…

Statistics Theory · Mathematics 2023-04-14 Yuan Gao , Riquan Zhang , Hansheng Wang

A general method is presented for deriving the limiting behavior of estimators that are defined as the values of parameters optimizing an empirical criterion function. The asymptotic behavior of such estimators is typically deduced from…

Statistics Theory · Mathematics 2008-12-18 Peter Radchenko

In Generalised Bayesian Inference (GBI), the learning rate and hyperparameters of the loss must be estimated. These inference-hyperparameters can't be estimated jointly with the other parameters, from the data, by giving them a prior.…

Methodology · Statistics 2026-05-18 Jeong Eun Lee , Sitong Liu , Geoff K. Nicholls

We introduce a non-autonomous generalization of spatial-temporal differentiations, and prove results about probabilistically and topologically generic behaviors of certain spatial-temporal differentiations generated by endomorphisms of…

Dynamical Systems · Mathematics 2022-04-25 Idris Assani , Aidan Young

For an affine two factor model, we study the asymptotic properties of the maximum likelihood and least squares estimators of some appearing parameters in the so-called subcritical (ergodic) case based on continuous time observations. We…

Statistics Theory · Mathematics 2014-06-17 Matyas Barczy , Leif Doering , Zenghu Li , Gyula Pap

The local physical properties of an isolated quantum statistical system in the stationary state reached long after a quench are generically described by the Gibbs ensemble, which involves only its Hamiltonian and the temperature as a…

Statistical Mechanics · Physics 2017-06-13 Laura Foini , Andrea Gambassi , Robert Konik , Leticia F. Cugliandolo

This article deals with Stein characterizations of probability distributions. We provide a general framework for interpreting these in terms of the parameters of the underlying distribution. In order to do so we introduce two concepts (a…

Probability · Mathematics 2011-12-02 Christophe Ley , Yvik Swan
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