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We propose a new test statistic based on a score process for determining the statistical significance of a putative signal that may be a small perturbation to a noisy experimental background. We derive the reference distribution for this…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Ramani S. Pilla , Catherine Loader , Cyrus Taylor

We study different fractional extensions of the Poisson process and generalized counting processes by introducing time-change represented by the inverse to the sums of stable and tempered stable subordinators. We state the governing…

Probability · Mathematics 2026-04-02 Lyudmyla Sakhno , Artem Storozhuk

Geometric quantiles are popular location functionals to build rank-based statistical procedures in multivariate settings. They are obtained through the minimization of a non-smooth convex objective function. As a result, the singularity of…

Statistics Theory · Mathematics 2026-02-11 Dimitri Konen , Gilles Stupfler

Hypothesis tests in models whose dimension far exceeds the sample size can be formulated much like the classical studentized tests only after the initial bias of estimation is removed successfully. The theory of debiased estimators can be…

Machine Learning · Statistics 2017-02-22 Jelena Bradic , Mladen Kolar

We consider a high quantile homogeneity test to determine whether a certain set of explanatory variables has homogeneous effects on different high quantiles of the response variable in the tail. To accommodate for situations under both the…

Statistics Theory · Mathematics 2026-05-12 Ting Zhang , Fangwei Wu , Jingying Gao

We focus on the construction of confidence corridors for multivariate nonparametric generalized quantile regression functions. This construction is based on asymptotic results for the maximal deviation between a suitable nonparametric…

Statistics Theory · Mathematics 2015-02-03 Shih-Kang Chao , Katharina Proksch , Holger Dette , Wolfgang Härdle

We derive normal approximation results for a class of stabilizing functionals of binomial or Poisson point process, that are not necessarily expressible as sums of certain score functions. Our approach is based on a flexible notion of the…

Probability · Mathematics 2022-10-20 Zhaoyang Shi , Krishnakumar Balasubramanian , Wolfgang Polonik

The empirical probability density function for the conditional distribution of the true value of Poisson distribution parameter on one measurement is constructed by computer experiment. The analysis of the obtained distributions confirms…

Data Analysis, Statistics and Probability · Physics 2009-11-10 S. I. Bityukov , V. A. Medvedev , V. V. Smirnova , Yu. V. Zernii

Existing methods for the estimation of stable distribution parameters, such as those based on sample quantiles, sample characteristic functions or maximum likelihood generally assume an independent sample. Little attention has been paid to…

Statistics Theory · Mathematics 2014-05-05 Adrian W. Barker

Diffusion models achieve remarkable generation quality, yet face a fundamental challenge known as memorization, where generated samples can replicate training samples exactly. We develop a theoretical framework to explain this phenomenon by…

Machine Learning · Computer Science 2026-03-31 Xinyu Zhou , Jiawei Zhang , Stephen J. Wright

This paper introduces an extension to the normal distribution through the polar method to capture bimodality and asymmetry, which are often observed characteristics of empirical data. The later two features are entirely controlled by a…

Statistics Theory · Mathematics 2020-08-31 Masoud Faridi , Majid Jafari Khaledi

We study the asymptotic behaviour of Bahadur-Kiefer processes that are generated by summing partial sums of (weakly or strongly dependent) random variables and their renewals. Known results for i.i.d. case will be extended to dependent…

Probability · Mathematics 2014-05-27 Endre Csáki , Miklós Csörgõ

This paper presents a new numerical scheme for simulating stochastic processes specified by their marginal distribution functions and covariance functions. Stochastic samples are firstly generated to automatically satisfy target marginal…

Computational Physics · Physics 2020-08-11 Zhibao Zheng

This paper is concerned with a robust estimator of the intensity of a stationary spatial point process. The estimator corresponds to the median of a jittered sample of the number of points, computed from a tessellation of the observation…

Statistics Theory · Mathematics 2015-05-28 Jean-François Coeurjolly

The paper considers nonparametric specification tests of quantile curves for a general class of nonstationary processes. Using Bahadur representation and Gaussian approximation results for nonstationary time series, simultaneous confidence…

Statistics Theory · Mathematics 2010-10-20 Zhou Zhou

Items in a test are often used as a basis for making decisions and such tests are therefore required to have good psychometric properties, like unidimensionality. In many cases the sum score is used in combination with a threshold to decide…

Methodology · Statistics 2020-07-14 Lourens Waldorp , Maarten Marsman , Denny Borsboom

We consider a measurable stationary Gaussian stochastic process. A criterion for testing hypotheses about the covariance function of such a process using estimates for its norm in the space $L_p(\mathbb {T}),\,p\geq1$, is constructed.

Probability · Mathematics 2015-03-19 Yuriy Kozachenko , Viktor Troshki

We use a characterization of symmetry in terms of extremal order statistics which enables to build several new nonparametric tests of symmetry. We discuss their limiting distributions and calculate their local exact Bahadur efficiency under…

Statistics Theory · Mathematics 2014-03-31 Ya. Yu. Nikitin , M. Ahsanullah

We consider a situation where the distribution of a random variable is being estimated by the empirical distribution of noisy measurements of that variable. This is common practice in, for example, teacher value-added models and other…

Econometrics · Economics 2021-12-08 Koen Jochmans , Martin Weidner

In many contexts such as queuing theory, spatial statistics, geostatistics and meteorology, data are observed at irregular spatial positions. One model of this situation involves considering the observation points as generated by a Poisson…

Statistics Theory · Mathematics 2007-08-07 Tucker McElroy , Dimitris N. Politis