English
Related papers

Related papers: Simultaneous Confidence Tubes for Comparison of Se…

200 papers

Given a pair of multivariate time-series data of the same length and dimensions, an approach is proposed to select variables and time intervals where the two series are significantly different. In applications where one time series is an…

Methodology · Statistics 2024-12-11 Kensuke Mitsuzawa , Margherita Grossi , Stefano Bortoli , Motonobu Kanagawa

In human microbiome studies, sequencing reads data are often summarized as counts of bacterial taxa at various taxonomic levels specified by a taxonomic tree. This paper considers the problem of analyzing two repeated measurements of…

Applications · Statistics 2017-02-17 Pixu Shi , Hongzhe Li

In this paper, we propose a general method for testing composite hypotheses. Our idea is to use confidence limits to define stopping and decision rules. The requirements of operating characteristic function can be satisfied by adjusting the…

Statistics Theory · Mathematics 2012-02-10 Xinjia Chen

We review the history of the parallel tempering simulation method. From its origins in data analysis, the parallel tempering method has become a standard workhorse of physiochemical simulations. We discuss the theory behind the method and…

Computational Physics · Physics 2017-09-13 David J. Earl , Michael W. Deem

Functional data analysis is proved to be useful in many scientific applications. The physical process is observed as curves and often there are several curves observed due to multiple subjects, providing the replicates in statistical sense.…

Methodology · Statistics 2018-01-30 Tapabrata Maiti , Abolfazl Safikhani , Ping-Shou Zhong

In this paper, we provide a general methodology to draw statistical inferences on individual signal coordinates or linear combinations of them in sparse phase retrieval. Given an initial estimator for the targeting parameter (some simple…

Methodology · Statistics 2020-09-29 Yisha Yao

Excessive reuse of test data has become commonplace in today's machine learning workflows. Popular benchmarks, competitions, industrial scale tuning, among other applications, all involve test data reuse beyond guidance by statistical…

Machine Learning · Computer Science 2019-05-30 Horia Mania , John Miller , Ludwig Schmidt , Moritz Hardt , Benjamin Recht

Monte Carlo experiments produce samples in order to estimate features of a given distribution. However, simultaneous estimation of means and quantiles has received little attention, despite being common practice. In this setting we…

Computation · Statistics 2020-04-24 Nathan Robertson , James M. Flegal , Dootika Vats , Galin L. Jones

This article presents methods for the construction of two-sided and one-sided simultaneous hyperbolic bands for the logistic and probit regression models when the predictor variable is restricted to a given interval. The bands are…

Statistics Theory · Mathematics 2016-04-06 Lucy Kerns

We consider nonparametric estimation of mean regression and conditional variance (or volatility) functions in nonlinear stochastic regression models. Simultaneous confidence bands are constructed and the coverage probabilities are shown to…

Statistics Theory · Mathematics 2008-08-08 Zhibiao Zhao , Wei Biao Wu

Minimum divergence methods are popular tools in a variety of statistical applications. We consider tubular model adequacy tests, and demonstrate that the new divergences that are generated in the process are very useful in robust…

Methodology · Statistics 2018-01-16 Abhik Ghosh , Ayanendranath Basu

When estimating causal effects using observational data, it is desirable to replicate a randomized experiment as closely as possible by obtaining treated and control groups with similar covariate distributions. This goal can often be…

Methodology · Statistics 2010-10-28 Elizabeth A. Stuart

Despite efforts to better understand the constraints that operate on single-step parallel (aka "package", "multiple") revision, very little work has been carried out on how to extend the model to the iterated case. A recent paper by…

Artificial Intelligence · Computer Science 2025-05-21 Jake Chandler , Richard Booth

We propose an extension to time series with several simultaneously measured variables of the nonlinearity test, which combines the redundancy -- linear redundancy approach with the surrogate data technique. For several variables various…

comp-gas · Physics 2009-10-28 Milan Paluš

In many applications involving multi-media data, the definition of similarity between items is integral to several key tasks, e.g., nearest-neighbor retrieval, classification, and recommendation. Data in such regimes typically exhibits…

Artificial Intelligence · Computer Science 2010-09-01 Brian McFee , Gert Lanckriet

This note revisits Steel's multiple comparison test which uses Wilcoxon statistics in pairwise comparisons of several treatment samples with a common control sample. It derives means, variances and covariances of the Wilcoxon statistics…

Statistics Theory · Mathematics 2023-08-14 F. W. Scholz

To identify statistically significant conclusions, it is proposed to simultaneously test hypotheses and alternatives. It is shown that, under the condition of free combination of hypotheses and alternatives, the closure method leads to…

Methodology · Statistics 2025-09-15 P. A. Koldanov , A. P. Koldanov

The problem of large-scale simultaneous hypothesis testing is re-visited. Bagging and subagging procedures are put forth with the purpose of improving the discovery power of the tests. The procedures are implemented in both simulated and…

Methodology · Statistics 2007-05-23 Dimitris N. Politis

Ratio of medians or other suitable quantiles of two distributions is widely used in medical research to compare treatment and control groups or in economics to compare various economic variables when repeated cross-sectional data are…

Methodology · Statistics 2017-10-26 Fabian Dunker , Stephan Klasen , Tatyana Krivobokova

This paper proposes the use of "multicalibration" to yield interpretable and reliable confidence scores for outputs generated by large language models (LLMs). Multicalibration asks for calibration not just marginally, but simultaneously…

Machine Learning · Statistics 2024-04-09 Gianluca Detommaso , Martin Bertran , Riccardo Fogliato , Aaron Roth