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Related papers: K-2 rotated goodness-of-fit for multivariate data

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We suggest several goodness-of-fit methods which are appropriate with Type-II right censored data. Our strategy is to transform the original observations from a censored sample into an approximately i.i.d. sample of normal variates and then…

Methodology · Statistics 2013-12-12 Christian Goldmann , Bernhard Klar , Simos G. Meintanis

This paper is about models for a vector of probabilities whose elements must have a multiplicative structure and sum to 1 at the same time; in certain applications, as basket analysis, these models may be seen as a constrained version of…

Statistics Theory · Mathematics 2018-04-17 Antonio Forcina

Comparing $K$-sample distributions is a fundamental problem in data science that arises in a wide variety of fields and applications. In this article, we introduce a maximum-of-differences approach to make such comparisons. Specifically, we…

Methodology · Statistics 2026-04-13 Wei Lan , Long Feng , Runze Li , Chih-Ling Tsai

Consider a population consisting of clusters of sampling units, evolving temporally, spatially, or according to other dynamics. We wish to monitor the evolution of its means, medians, or other parameters. For administrative convenience and…

Methodology · Statistics 2020-04-30 Jiahua Chen , Yukun Liu , James Zidek

Although models for count data with over-dispersion have been widely considered in the literature, models for under-dispersion -- the opposite phenomenon -- have received less attention as it is only relatively common in particular research…

This paper presents and examines computationally convenient goodness-of-fit tests for the family of generalized Poisson distributions, which encompasses notable distributions such as the Compound Poisson and the Katz distributions. The…

Methodology · Statistics 2024-11-21 A. Batsidis , B. Milošević , M. D. Jiménez-Gamero

Application of the exact statistical inference frequently leads to a non-standard probability distributions of the considered estimators or test statistics. The exact distributions of many estimators and test statistics can be specified by…

Computation · Statistics 2018-01-09 Viktor Witkovský

We present new families of goodness-of-fit tests of uniformity on a full-dimensional set $W\subset\R^d$ based on statistics related to edge lengths of random geometric graphs. Asymptotic normality of these statistics is proven under the…

Statistics Theory · Mathematics 2020-07-20 Bruno Ebner , Franz Nestmann , Matthias Schulte

Model-free knockoffs is a recently proposed technique for identifying covariates that is likely to have an effect on a response variable. The method is an efficient method to control the false discovery rate in hypothesis tests for separate…

Methodology · Statistics 2019-03-29 Lars Holden , Kristoffer Hellton

The goodness-of-fit test for discrimination of two tail distribution using higher order statistics is proposed. The consistency of proposed test is proved for two different alternatives. We do not assume belonging the corresponding…

Statistics Theory · Mathematics 2017-02-21 Igor Vladimirovich Rodionov

Assessing goodness of fit to a given distribution plays an important role in computational statistics. The Probability integral transformation (PIT) can be used to convert the question of whether a given sample originates from a reference…

Methodology · Statistics 2022-12-22 Teemu Säilynoja , Paul-Christian Bürkner , Aki Vehtari

Data depth provides a centre-outward ordering for multivariate data. Recently, some univariate GoF tests based on data depth have been studied by Li (2018). This paper discusses some univariate goodness of fit tests based on centre-outward…

Methodology · Statistics 2024-05-14 Rahul Singh

We consider the problem of function estimation in the case where the data distribution may shift between training and test time, and additional information about it may be available at test time. This relates to popular scenarios such as…

Machine Learning · Statistics 2013-06-05 Bernhard Schölkopf , Dominik Janzing , Jonas Peters , Kun Zhang

Permutation methods are commonly used to test significance of regressors of interest in general linear models (GLMs) for functional (image) data sets, in particular for neuroimaging applications as they rely on mild assumptions. Permutation…

Methodology · Statistics 2021-11-23 Tomas Mrkvicka , Mari Myllymaki , Mikko Kuronen , Naveen Naidu Narisetty

The paper discusses a test for the hypothesis that a random sample comes from the Cauchy distribution. The test statistics is derived from a characterization and is based on the characteristic function. Properties of the test are discussed…

Statistics Theory · Mathematics 2016-11-21 Emanuele Taufer

Cross validation residuals are well known for the ordinary least squares model. Here leave-M-out cross validation is extended to generalised least squares. The relationship between cross validation residuals and Cook's distance is…

Methodology · Statistics 2018-09-06 Ingrid Annette Baade

Gathering observational data for medical decision-making often involves uncertainties arising from both type I (false positive)and type II (false negative) errors. In this work, we develop a statistical model to study how medical…

Applications · Statistics 2025-10-21 Lucas Böttcher , Maria R. D'Orsogna , Tom Chou

Analogues of the frequentist chi-square and F tests are proposed for testing goodness-of-fit and consistency for Bayesian models. Simple examples exhibit these tests' detection of inconsistency between consecutive experiments with identical…

Instrumentation and Methods for Astrophysics · Physics 2016-03-16 L. B. Lucy

We study the question of identity testing for structured distributions. More precisely, given samples from a {\em structured} distribution $q$ over $[n]$ and an explicit distribution $p$ over $[n]$, we wish to distinguish whether $q=p$…

Data Structures and Algorithms · Computer Science 2014-10-10 Ilias Diakonikolas , Daniel M. Kane , Vladimir Nikishkin

We develop here several goodness-of-fit tests for testing the k-monotonicity of a discrete density, based on the empirical distribution of the observations. Our tests are non-parametric, easy to implement and are proved to be asymptotically…

Methodology · Statistics 2017-08-30 Jade Giguelay , Sylvie Huet