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A new method based on the rejection sampling for finding statistical tests is proposed. This method is conceptually intuitive, easy to implement, and applicable for arbitrary dimension. To illustrate its potential applicability, three…

Methodology · Statistics 2026-03-11 Markku Kuismin

We consider nonparametric sequential hypothesis testing problem when the distribution under the null hypothesis is fully known but the alternate hypothesis corresponds to some other unknown distribution with some loose constraints. We…

Information Theory · Computer Science 2013-11-15 Shouvik Ganguly , K Sahasranand , Vinod Sharma

Upon compressing perceptually relevant signals, conventional quantization generally results in unnatural outcomes at low rates. We propose distribution preserving quantization (DPQ) to solve this problem. DPQ is a new quantization concept…

Information Theory · Computer Science 2011-08-19 Minyue Li , Janusz Klejsa , W. Bastiaan Kleijn

The frequency response function (FRF) is a typical way to describe the outcome of experiments where posture control is perturbed with an external stimulus. The FRF is an empirical transfer function between an input stimulus and the induced…

Applications · Statistics 2025-06-02 Vittorio Lippi

We investigate the statistical and computational limits of latent Diffusion Transformers (DiTs) under the low-dimensional linear latent space assumption. Statistically, we study the universal approximation and sample complexity of the DiTs…

Machine Learning · Statistics 2024-11-01 Jerry Yao-Chieh Hu , Weimin Wu , Zhao Song , Han Liu

Channel estimation is one of the most important parts in current mobile communication systems. Among the huge contributions in channel estimation studies, the discrete Fourier transform (DFT)-based channel estimation has attracted lots of…

Information Theory · Computer Science 2015-04-29 H. Yu , C. Yang

The notion of concept drift refers to the phenomenon that the data generating distribution changes over time; as a consequence machine learning models may become inaccurate and need adjustment. In this paper we consider the problem of…

Machine Learning · Computer Science 2022-05-16 Fabian Hinder , André Artelt , Valerie Vaquet , Barbara Hammer

Deep-learning (DL) has emerged as a powerful machine-learning technique for several classic problems encountered in generic wireless communications. Specifically, random Fourier Features (RFF) based deep-learning has emerged as an…

Information Theory · Computer Science 2021-01-14 Rangeet Mitra , Georges Kaddoum

Although several nonparametric tests are available for testing population identical distributions or equal means in multiple groups problem, the Van der Waerden test has asymptotically the same efficiency as the classical one-way analysis…

Methodology · Statistics 2022-03-07 Elsayed Elamir

Feature Transformation (FT) crafts new features from original ones via mathematical operations to enhance dataset expressiveness for downstream models. However, existing FT methods exhibit critical limitations: discrete search struggles…

Machine Learning · Computer Science 2025-05-22 Nanxu Gong , Zijun Li , Sixun Dong , Haoyue Bai , Wangyang Ying , Xinyuan Wang , Yanjie Fu

Many flexible families of positive random variables exhibit non-closed forms of the density and distribution functions and this feature is considered unappealing for modelling purposes. However, such families are often characterized by a…

Statistics Theory · Mathematics 2025-06-09 Lucio Barabesi , Antonio Di Noia , Marzia Marcheselli , Caterina Pisani , Luca Pratelli

Spatial interaction between two or more classes or species has important implications in various fields and causes multivariate patterns such as segregation or association. Segregation occurs when members of a class or species are more…

Methodology · Statistics 2009-02-09 Elvan Ceyhan

We propose new classes of tests for the Pareto type I distribution using the empirical characteristic function. These tests are $U$ and $V$ statistics based on a characterisation of the Pareto distribution involving the distribution of the…

Methodology · Statistics 2023-01-24 L. Ndwandwe , J. S. Allison , M. Smuts , I. J. H. Visagie

Existing audio-text retrieval (ATR) methods are essentially discriminative models that aim to maximize the conditional likelihood, represented as p(candidates|query). Nevertheless, this methodology fails to consider the intrinsic data…

Sound · Computer Science 2024-10-18 Yifei Xin , Xuxin Cheng , Zhihong Zhu , Xusheng Yang , Yuexian Zou

The distance transform (DT) and its many variations are ubiquitous tools for image processing and analysis. In many imaging scenarios, the images of interest are corrupted by noise. This has a strong negative impact on the accuracy of the…

Computer Vision and Pattern Recognition · Computer Science 2020-09-14 Johan Öfverstedt , Joakim Lindblad , Nataša Sladoje

The Fisher randomization test (FRT) is appropriate for any test statistic, under a sharp null hypothesis that can recover all missing potential outcomes. However, it is often sought after to test a weak null hypothesis that the treatment…

Methodology · Statistics 2020-11-09 Jason Wu , Peng Ding

The random variate m is, in combinatorics, a basis for comparing permutations, as well as the solution to a centuries-old riddle involving the mishandling of hats. In statistics, m is the test statistic for a disused null hypothesis…

Other Statistics · Statistics 2020-10-19 Michael C. Nelson

In this paper, we propose a new test for checking the parametric form of the conditional variance based on distance covariance in nonlinear and nonparametric regression models. Inherit from the nice properties of distance covariance, our…

Methodology · Statistics 2022-05-19 Yue Hu , Haiqi Li , Falong Tan

The fundamentals of Fourier Transform are presented, with analytical solutions derived for Continuous Fourier Transform (CFT) of truncated signals, to benchmark against Fast Fourier Transform (FFT). Certain artifacts from FFT were…

Applied Physics · Physics 2019-07-03 K. H. H. Goh

The frequency response function (FRF) is an established way to describe the outcome of experiments in posture control literature. The FRF is an empirical transfer function between an input stimulus and the induced body segment sway profile,…

Signal Processing · Electrical Eng. & Systems 2025-01-31 Vittorio Lippi