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Multidimensional efficiency maps are commonly used in high energy physics experiments to mitigate the limitations in the generation of large samples of simulated events. Binned multidimensional efficiency maps are however strongly limited…

High Energy Physics - Experiment · Physics 2020-05-19 C. Badiali , F. A. Di Bello , G. Frattari , E. Gross , V. Ippolito , M. Kado , J. Shlomi

We aim to make inferences about a smooth, finite-dimensional parameter by fusing data from multiple sources together. Previous works have studied the estimation of a variety of parameters in similar data fusion settings, including in the…

Methodology · Statistics 2025-02-03 Sijia Li , Alex Luedtke

We present a theoretical framework to quantify statistical uncertainties in covariant density functional theory (CDFT) for both nuclear matter and finite nuclei, based on a relativistic point-coupling energy density functional (EDF). By…

Nuclear Theory · Physics 2026-04-10 X. Zhang , C. C. Wang , C. R. Ding , J. M. Yao

To establish the electron energy distribution function (EEDF), the second derivative of a Langmuir probe current-voltage (I-V) characteristic is numerically integrated using the Tikhonov singular value decomposition regularized method. A…

Plasma Physics · Physics 2009-11-10 Cesar Gutierrez-Tapia , Hector Flores Llamas

For the multi-sample equal covariance function (ECF) testing problem, Zhang (2013) proposed an $L^{2}$-norm based test. However, its asymptotic power and finite sample performance have not been studied. In this paper, its asymptotic power…

Statistics Theory · Mathematics 2016-09-15 Jia Guo , Jin-Ting Zhang

We consider the goodness of fit testing problem for ergodic diffusion processes. The basic hypothesis is supposed to be simple. The diffusion coefficient is known and the alternatives are described by the different trend coefficients. We…

Statistics Theory · Mathematics 2009-03-27 Yury A. Kutoyants

This paper presents a class of new algorithms for distributed statistical estimation that exploit divide-and-conquer approach. We show that one of the key benefits of the divide-and-conquer strategy is robustness, an important…

Statistics Theory · Mathematics 2018-08-29 Stanislav Minsker , Nate Strawn

Energy-based models (EBMs) are versatile density estimation models that directly parameterize an unnormalized log density. Although very flexible, EBMs lack a specified normalization constant of the model, making the likelihood of the model…

Machine Learning · Computer Science 2024-02-20 Louis Grenioux , Éric Moulines , Marylou Gabrié

We present alphaPDE, a new multivariate analysis technique for parameter estimation. The method is based on a direct construction of joint probability densities of known variables and the parameters to be estimated. We show how posterior…

Data Analysis, Statistics and Probability · Physics 2009-11-07 B. Knuteson , H. Miettinen , L. Holmstrom

Assume a (semi)parametrically efficient estimator is given of the Euclidean parameter in a (semi)parametric model. A submodel is obtained by constraining this model in that a continuously differentiable function of the Euclidean parameter…

Statistics Theory · Mathematics 2016-06-27 Chris A. J. Klaassen , Nanang Susyanto

Experiments often yield non-identically distributed data for statistical analysis. Tests of hypothesis under such set-ups are generally performed using the likelihood ratio test, which is non-robust with respect to outliers and model…

Statistics Theory · Mathematics 2017-07-25 Abhik Ghosh , Ayanendranath Basu

We obtain a Bahadur representation for sample quantiles of nonlinear functional of Gaussian sequences with correlation function decreasing as $k^{-\alpha}$ for some $\alpha > 0$. This representation is derived under a mimimal assumption.

Statistics Theory · Mathematics 2008-09-30 Jean-François Coeurjolly

A new anchor-based optimization method of defining the energy density functionals (EDFs) is proposed. In this approach, the optimization of the parameters of EDF is carried out for the selected set of spherical anchor nuclei the physical…

Nuclear Theory · Physics 2023-04-19 A. Taninah , A. V. Afanasjev

A novel operational method for estimating the efficiency of quantum state tomography protocols is suggested. It is based on a-priori estimation of the quality of an arbitrary protocol by means of universal asymptotic fidelity distribution…

Quantum Physics · Physics 2015-05-18 Yu. I. Bogdanov , G. Brida , M. Genovese , S. P. Kulik , E. V. Moreva , A. P. Shurupov

We are interested in the problem of robust parametric estimation of a density from $n$ i.i.d. observations. By using a practice-oriented procedure based on robust tests, we build an estimator for which we establish non-asymptotic risk…

Statistics Theory · Mathematics 2016-03-31 Mathieu Sart

Due to the broad applications of elliptical models, there is a long line of research on goodness-of-fit tests for empirically validating them. However, the existing literature on this topic is generally confined to low-dimensional settings,…

Statistics Theory · Mathematics 2025-03-04 Siyao Wang , Miles E. Lopes

This paper develops a smooth test of goodness-of-fit for elliptical distributions. The test is adaptively omnibus, invariant to affine-linear transformations and has a convenient expression that can be broken into components. These…

Statistics Theory · Mathematics 2019-02-12 Gilles R. Ducharme , Pierre Lafaye de Micheaux

We consider the error distribution in functional linear models with scalar response and functional covariate. Different asymptotic expansions of the empirical distribution function and the empirical characteristic function based on…

Methodology · Statistics 2025-12-01 Natalie Neumeyer , Leonie Selk

This paper extends a recently proposed family of EDF-based goodness-of-fit procedures for the hypercube $[0,1]^p$ - the m-test and the s-test - which are based on a unique deconstruction of the $p$-parameter Brownian sheet into independent…

Statistics Theory · Mathematics 2026-05-19 Alejandra Cabaña , Enrique M. Cabaña

Not many tests exist for testing the equality for two or more multivariate distributions with compositional data, perhaps due to their constrained sample space. At the moment, there is only one test suggested that relies upon random…

Methodology · Statistics 2025-12-12 Volkan Sevinc , Michail Tsagris