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The proposed Circular statistics-based Inter-Microphone Phase difference estimation Localizer (CIMPL) method is tailored toward binaural hearing aid systems with microphone arrays in each unit. The method utilizes the circular statistics…

In this paper I consider improving the KernelSHAP algorithm. I suggest to use the Wallenius' noncentral hypergeometric distribution for sampling the number of coalitions and perform sampling without replacement, so that the KernelSHAP…

Methodology · Statistics 2026-01-15 Fredrik Lohne Aanes

This paper investigates a partially linear spatial autoregressive panel data model that incorporates fixed effects, constant and time-varying regression coefficients, and a time-varying spatial lag coefficient. A two-stage least squares…

Statistics Theory · Mathematics 2024-10-15 Lingling Tian , Chuanhua Wei , Mixia Wu

Agreement coefficients provide a fundamental framework for quantifying the concordance between two or more measurement methods applied to the same continuous variable. Unlike correlation, which measures the strength of a linear…

Methodology · Statistics 2026-04-28 Ronny Vallejos

We derive a fully computable aposteriori error estimator for a Galerkin finite element solution of the wave equation with explicit leapfrog time-stepping. Our discrete formulation accommodates both time evolving meshes and leapfrog based…

Numerical Analysis · Mathematics 2025-06-27 Marcus J. Grote , Omar Lakkis , Carina Santos

This paper proposes methods for likelihood-based inference in multivariate linear regressions when the correlation matrix of the responses is separable; that is, it has a Kronecker product structure, but the variances are unrestricted. The…

Computation · Statistics 2026-04-16 Karl Oskar Ekvall

In this article, we consider identification, estimation, and inference procedures for treatment effect parameters using Difference-in-Differences (DiD) with (i) multiple time periods, (ii) variation in treatment timing, and (iii) when the…

Econometrics · Economics 2020-12-02 Brantly Callaway , Pedro H. C. Sant'Anna

We present a new algorithm for estimating the star discrepancy of arbitrary point sets. Similar to the algorithm for discrepancy approximation of Winker and Fang [SIAM J. Numer. Anal. 34 (1997), 2028--2042] it is based on the optimization…

Data Structures and Algorithms · Computer Science 2021-09-21 Michael Gnewuch , Magnus Wahlström , Carola Winzen

Accurate conditional prediction in the regression setting plays an important role in many real-world problems. Typically, a point prediction often falls short since no attempt is made to quantify the prediction accuracy. Classically, under…

Methodology · Statistics 2025-09-04 Kejin Wu , Dimitris N. Politis

The logistic regression analysis proposed by Schouten et al. (Stat Med. 1993;12:1733-1745) has been a standard method in current statistical analysis of case-cohort studies, and it enables effective estimation of risk ratio from selected…

Methodology · Statistics 2023-01-19 Hisashi Noma

Starting from a recent a posteriori error estimator for the finite element solution of the wave equation with explicit time-stepping [Grote, Lakkis, Santos, 2024], we devise a space-time adaptive strategy which includes both time evolving…

Numerical Analysis · Mathematics 2026-01-07 Marcus J. Grote , Omar Lakkis , Carina S. Santos

Actigraphy has been widely used for the analysis of circadian rhythm. Current practice applies regression analysis to data from multiple days to estimate the circadian phase. This paper presents a filtering method for online processing of…

Systems and Control · Computer Science 2018-04-03 Wei Qiao , Kyle Altman , Agung Julius , Bernard Possidente , John T. Wen

Modern statistical analysis often encounters datasets with large sizes. For these datasets, conventional estimation methods can hardly be used immediately because practitioners often suffer from limited computational resources. In most…

Methodology · Statistics 2023-04-14 Shuyuan Wu , Xuening Zhu , Hansheng Wang

The squared Wasserstein distance is a natural quantity to compare probability distributions in a non-parametric setting. This quantity is usually estimated with the plug-in estimator, defined via a discrete optimal transport problem which…

Optimization and Control · Mathematics 2020-10-30 Lenaic Chizat , Pierre Roussillon , Flavien Léger , François-Xavier Vialard , Gabriel Peyré

In this paper, we propose a novel bootstrap algorithm that is more efficient than existing methods for approximating the distribution of the factor-augmented regression estimator for a rotated parameter vector. The regression is augmented…

Methodology · Statistics 2025-10-02 Peiyun Jiang , Takashi Yamagata

Statistical estimation and inference for marginal hazard models with varying coefficients for multivariate failure time data are important subjects in survival analysis. A local pseudo-partial likelihood procedure is proposed for estimating…

Statistics Theory · Mathematics 2009-09-29 Jianwen Cai , Jianqing Fan , Haibo Zhou , Yong Zhou

Estimating entropy and mutual information consistently is important for many machine learning applications. The Kozachenko-Leonenko (KL) estimator (Kozachenko & Leonenko, 1987) is a widely used nonparametric estimator for the entropy of…

Statistics Theory · Mathematics 2016-07-22 Shashank Singh , Barnabás Póczos

Computing the agreement between two continuous sequences is of great interest in statistics when comparing two instruments or one instrument with a gold standard. The probability of agreement (PA) quantifies the similarity between two…

Methodology · Statistics 2025-05-20 Jonathan Acosta , Ronny Vallejos , Aaron M. Ellison , Felipe Osorio , Mario de Castro

Fitting parametric models by optimizing frequency domain objective functions is an attractive approach of parameter estimation in time series analysis. Whittle estimators are a prominent example in this context. Under weak conditions and…

Statistics Theory · Mathematics 2021-07-26 Jens-Peter Kreiss , Efstathios Paparoditis

We describe and compare several post-correlation radio frequency interference classification methods. As data sizes of observations grow with new and improved telescopes, the need for completely automated, robust methods for radio frequency…

Instrumentation and Methods for Astrophysics · Physics 2010-07-14 A. R. Offringa , A. G. de Bruyn , M. Biehl , S. Zaroubi , G. Bernardi , V. N. Pandey
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