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This study presents two new algorithms for solving linear stochastic bandit problems. The proposed methods use an approach from non-parametric statistics called bootstrapping to create confidence bounds. This is achieved without making any…

Machine Learning · Statistics 2016-05-05 Nandan Sudarsanam , Balaraman Ravindran

The ratio of the hazard functions of two populations or two strata of a single population plays an important role in time-to-event analysis. Cox regression is commonly used to estimate the hazard ratio under the assumption that it is…

Methodology · Statistics 2022-07-13 Yujian Wu , Ted Westling

A fixed-design residual bootstrap method is proposed for the two-step estimator of Francq and Zako\"ian (2015) associated with the conditional Value-at-Risk. The bootstrap's consistency is proven for a general class of volatility models and…

Econometrics · Economics 2023-08-16 Eric Beutner , Alexander Heinemann , Stephan Smeekes

We propose simultaneous confidence bands of the hyperbolic-type for the contrasts between several nonlinear (curvilinear) regression curves. The critical value of a confidence band is determined from the distribution of the maximum of a…

Statistics Theory · Mathematics 2017-01-11 Xiaolei Lu , Satoshi Kuriki

This paper investigates the effects of smoothed bootstrap iterations on coverage probabilities of smoothed bootstrap and bootstrap-t confidence intervals for population quantiles, and establishes the optimal kernel bandwidths at various…

Statistics Theory · Mathematics 2007-06-13 Yvonne H. S. Ho , Stephen M. S. Lee

In this communication, we introduce a new statistical model and study its various mathematical properties. The expressions for hazard rate, reversed hazard rate, and odd functions are provided. We explore the asymptotic behaviors of the…

Methodology · Statistics 2023-04-24 Tuhin Subhra Mahatao , Subhankar Dutta , Suchandan Kayal

This paper presents a new conformal method for generating simultaneous forecasting bands guaranteed to cover the entire path of a new random trajectory with sufficiently high probability. Prompted by the need for dependable uncertainty…

Machine Learning · Statistics 2024-05-16 Yanfei Zhou , Lars Lindemann , Matteo Sesia

This paper introduces the new data-dependent multiplier bootstrap for non-parametric analysis of survival data, possibly subject to competing risks. The new resampling procedure includes both the general wild bootstrap and the weird…

Statistics Theory · Mathematics 2015-08-25 Dennis Dobler , Jan Beyersmann , Markus Pauly

We show that bootstrap methods based on the positivity of probability measures provide a systematic framework for studying both synchronous and asynchronous nonequilibrium stochastic processes on infinite lattices. First, we formulate…

Statistical Mechanics · Physics 2025-11-12 Minjae Cho

The role played by the composite analogue of the log likelihood ratio in hypothesis testing and in setting confidence regions is not as prominent as it is in the canonical likelihood setting, since its asymptotic distribution depends on the…

Methodology · Statistics 2013-01-30 Nicola Lunardon

Based on a progressively type-II censored sample from the exponential distribution with unknown location and scale parameter, confidence bands are proposed for the underlying distribution function by using confidence regions for the…

Statistics Theory · Mathematics 2021-06-08 Stefan Bedbur , Fabian Mies

Subsampling and block-based bootstrap methods have been used in a wide range of inference problems for time series. To accommodate the dependence, these resampling methods involve a bandwidth parameter, such as subsampling window width and…

Statistics Theory · Mathematics 2012-04-05 Xiaofeng Shao , Dimitris N. Politis

This study focuses on finite-sample inference on the non-linear Bures-Wasserstein manifold and introduces a generalized bootstrap procedure for estimating Bures-Wasserstein barycenters. We provide non-asymptotic statistical guarantees for…

Statistics Theory · Mathematics 2024-11-26 Alexey Kroshnin , Vladimir Spokoiny , Alexandra Suvorikova

Income inequality measures are often used as an indication of economic health. How to obtain reliable confidence intervals for these measures based on sampled data has been studied extensively in recent years. To preserve confidentiality,…

Applications · Statistics 2019-07-22 Dilanka S. Dedduwakumara , Luke A. Prendergast

We study an AMOC time series model with an abrupt change in the mean and dependent errors that fulfill certain mixing conditions. We obtain confidence intervals for the unknown change-point via bootstrapping methods. Precisely we use a…

Statistics Theory · Mathematics 2008-10-30 Marie Huskova , Claudia Kirch

Consider $M$-estimation in a semiparametric model that is characterized by a Euclidean parameter of interest and an infinite-dimensional nuisance parameter. As a general purpose approach to statistical inferences, the bootstrap has found…

Statistics Theory · Mathematics 2011-02-04 Guang Cheng , Jianhua Z. Huang

In the context of the widely used competing risks set-up we discuss different inference procedures for testing equality of two cumulative incidence functions, where the data may be subject to independent right-censoring or left-truncation.…

Statistics Theory · Mathematics 2015-10-13 Dennis Dobler , Markus Pauly

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

We propose a new method to construct confidence intervals for quantities that are associated with a stationary time series, which avoids direct estimation of the asymptotic variances. Unlike the existing tuning-parameter-dependent…

Methodology · Statistics 2010-05-13 Xiaofeng Shao

In observational studies of survival time featuring a binary time-dependent treatment, the hazard ratio (an instantaneous measure) is often used to represent the treatment effect. However, investigators are often more interested in the…

Methodology · Statistics 2020-05-21 Yun Li , Douglas E. Schaubel , Kevin He