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The empirical copula process plays a central role for statistical inference on copulas. Recently, Segers (2011) investigated the asymptotic behavior of this process under non-restrictive smoothness assumptions for the case of i.i.d. random…

Statistics Theory · Mathematics 2011-11-14 Axel Bücher , Stanislav Volgushev

The construction of the simultaneous confidence bands for the integrated hazard function is considered. The Nelson--Aalen estimator is used. The simultaneous confidence bands based on bootstrap methods are presented. Two methods of…

Statistics Theory · Mathematics 2007-06-13 Anna Dudek , Maciej Gocwin , Jacek Leskow

An algorithm is described that enables efficient deterministic approximate computation of the bootstrap distribution for any linear bootstrap method $T_n^*$, alleviating the need for repeated resampling from observations (resp.…

Methodology · Statistics 2019-04-10 Thomas Pitschel

We reexamine the recently introduced basis-set correction theory based on density-functional theory consisting in correcting the basis-set incompleteness error of wave-function methods using a density functional. We use a one-dimensional…

Chemical Physics · Physics 2022-02-16 Diata Traore , Emmanuel Giner , Julien Toulouse

We present a hybrid quantum-classical framework for simulating generic matrix functions more amenable to early fault-tolerant quantum hardware than standard quantum singular-value transformations. The method is based on randomization over…

Quantum Physics · Physics 2024-11-28 Allan Tosta , Thais de Lima Silva , Giancarlo Camilo , Leandro Aolita

Functional quadratic regression models postulate a polynomial relationship between a scalar response rather than a linear one. As in functional linear regression, vertical and specially high-leverage outliers may affect the classical…

Methodology · Statistics 2023-05-30 Graciela Boente , Daniela Parada

In this paper we develop statistical inference tools for high dimensional functional time series. We introduce a new concept of physical dependent processes in the space of square integrable functions, which adopts the idea of basis…

Statistics Theory · Mathematics 2020-03-16 Zhou Zhou , Holger Dette

This paper deals with the problem of estimating the level sets $L(c)= \{F(x) \geq c \}$, with $c \in (0,1)$, of an unknown distribution function $F$ on \mathbb{R}^d_+$. A plug-in approach is followed. That is, given a consistent estimator…

Statistics Theory · Mathematics 2012-02-13 Elena Di Bernadino , Thomas Laloë

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

Asymptotic inference using functional principal component regression (FPCR) has long been considered difficult, largely because, upon any scalar scaling, the FPCR estimator fails to satisfy a central limit theorem, leading to the prevailing…

Statistics Theory · Mathematics 2026-03-16 Hyemin Yeon

While widely used as a general method for uncertainty quantification, the bootstrap method encounters difficulties that raise concerns about its validity in practical applications. This paper introduces a new resampling-based method, termed…

Methodology · Statistics 2024-08-30 Yiran Jiang , Chuanhai Liu , Heping Zhang

The Highly-Adaptive-LASSO Targeted Minimum Loss Estimator (HAL-TMLE) is an efficient plug-in estimator of a pathwise differentiable parameter in a statistical model that at minimal (and possibly only) assumes that the sectional variation…

Statistics Theory · Mathematics 2020-02-12 Weixin Cai , Mark van der Laan

This paper focuses on nonparametric statistical inference of the hazard rate function of discrete distributions based on $\delta$-record data. We derive the explicit expression of the maximum likelihood estimator and determine its exact…

Statistics Theory · Mathematics 2025-04-03 Martín Alcalde , Miguel Lafuente , F. Javier López , Lina Maldonado , Gerardo Sanz

New estimators for the mean and the covariance function for partially observed functional data are proposed using a detour via the fundamental theorem of calculus. The new estimators allow for a consistent estimation of the mean and…

Methodology · Statistics 2018-08-01 Dominik Liebl , Stefan Rameseder

The joint alignment of multivariate functional data plays an important role in various fields such as signal processing, neuroscience and medicine, including the statistical analysis of data from wearable devices. Traditional methods often…

Signal Processing · Electrical Eng. & Systems 2023-12-18 Vi Thanh Pham , Jonas Bille Nielsen , Klaus Fuglsang Kofoed , Jørgen Tobias Kühl , Andreas Kryger Jensen

Density functional theory is a successful branch of numerical simulations of quantum systems. While the foundations are rigorously defined, the universal functional must be approximated resulting in a `semi'-ab initio approach. The search…

Quantum Physics · Physics 2017-11-22 James Daniel Whitfield , Norbert Schuch , Frank Verstraete

For covariance test in functional data analysis, existing methods are developed only for fully observed curves, whereas in practice, trajectories are typically observed discretely and with noise. To bridge this gap, we employ a…

Methodology · Statistics 2026-04-20 Yang Zhou , Jin Yang , Fang Yao

The problem of constructing a simultaneous confidence surface for the 2-dimensional mean function of a non-stationary functional time series is challenging as these bands can not be built on classical limit theory for the maximum absolute…

Statistics Theory · Mathematics 2024-11-27 Holger Dette , Weichi Wu

Under certain general conditions, an explicit formula to compute the greatest delta-epsilon function of a continuous function is given. From this formula, a new way to analyze the uniform continuity of a continuous function is given.…

General Mathematics · Mathematics 2017-10-12 César Adolfo Hernández Melo

This paper addresses the problem of providing robust estimators under a functional logistic regression model. Logistic regression is a popular tool in classification problems with two populations. As in functional linear regression,…

Methodology · Statistics 2023-08-16 Graciela Boente , Marina Valdora
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