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Related papers: Goodness-of-fit test for the bivariate Hermite dis…

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The bivariate Poisson distribution is commonly used to model bivariate count data. In this paper we study a goodness-of-fit test for this distribution. We also provide a review of the existing tests for the bivariate Poisson distribution,…

Statistics Theory · Mathematics 2019-02-26 Francisco Novoa-Muñoz

A consistent goodness-of-fit test for distributional regression is introduced. The test statistic is based on a process that traces the difference between a nonparametric and a semi-parametric estimate of the marginal distribution function…

Methodology · Statistics 2025-10-10 Gitte Kremling , Gerhard Dikta

We consider the goodness of fit testing problem for linear stochastic differential equation (Ornstein-Uhlenbeck process). The basic hypothesis is supposed to be composite with two-dimensional unknown parameter. We study two goodness of fit…

Statistics Theory · Mathematics 2013-05-16 Yury A. Kutoyants

In this work, the distributional properties of the goodness-of-fit term in likelihood-based information criteria are explored. These properties are then leveraged to construct a novel goodness-of-fit test for normal linear regression models…

Methodology · Statistics 2023-09-20 Scott H. Koeneman , Joseph E. Cavanaugh

We consider the problem of goodness-of-fit testing for a model that has at least one unknown parameter that cannot be eliminated by transformation. Examples of such problems can be as simple as testing whether a sample consists of…

Methodology · Statistics 2021-04-28 Sean van der Merwe

We propose a nonparametric statistical test for goodness-of-fit: given a set of samples, the test determines how likely it is that these were generated from a target density function. The measure of goodness-of-fit is a divergence…

Machine Learning · Statistics 2016-09-28 Kacper Chwialkowski , Heiko Strathmann , Arthur Gretton

We consider the goodness of fit testing problem for ergodic diffusion processes. The basic hypothesis is supposed to be simple. The diffusion coefficient is known and the alternatives are described by the different trend coefficients. We…

Statistics Theory · Mathematics 2009-03-27 Yury A. Kutoyants

A goodness-of-fit test for one-parameter count distributions with finite second moment is proposed. The test statistic is derived from the $L^1$ distance of a function of the probability generating function of the model under the null…

Statistics Theory · Mathematics 2024-06-11 Antonio Di Noia , Lucio Barabesi , Marzia Marcheselli , Caterina Pisani , Luca Pratelli

A problem of goodness-of-fit test for ergodic diffusion processes is presented. In the null hypothesis the drift of the diffusion is supposed to be in a parametric form with unknown shift parameter. Two Cramer-Von Mises type test statistics…

Statistics Theory · Mathematics 2012-03-30 Ilia Negri , Li Zhou

We introduce the \textit{almost goodness-of-fit} test, a procedure to assess whether a (parametric) model provides a good representation of the probability distribution generating the observed sample. Specifically, given a distribution…

Methodology · Statistics 2025-10-15 Amparo Baíllo , Javier Cárcamo

We study the conditional distribution of goodness of fit statistics of the Cram\'{e}r--von Mises type given the complete sufficient statistics in testing for exponential family models. We show that this distribution is close, in large…

Statistics Theory · Mathematics 2012-07-26 Richard A. Lockhart

The process comparing the empirical cumulative distribution function of the sample with a parametric estimate of the cumulative distribution function is known as the empirical process with estimated parameters and has been extensively…

Methodology · Statistics 2012-10-08 Ivan Kojadinovic , Jun Yan

The Functional Linear Model with Functional Response (FLMFR) is one of the most fundamental models to assess the relation between two functional random variables. In this paper, we propose a novel goodness-of-fit test for the FLMFR against…

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

We consider a linear regression model and propose an omnibus test to simultaneously check the assumption of independence between the error and the predictor variables, and the goodness-of-fit of the parametric model. Our approach is based…

Methodology · Statistics 2014-05-06 Arnab Sen , Bodhisattva Sen

We introduce a new goodness-of-fit test for count data on $\mathbb{N}$ for the Zeta distribution with unknown parameter. The test is built on a Stein-type characterization that uses, as Stein operator, the infinitesimal generator of a…

Statistics Theory · Mathematics 2026-01-01 Bruno Ebner , Daniel Hlubinka

Assessing model adequacy is a crucial step in regression analysis, ensuring the validity of statistical inferences. For Generalized Functional Linear Models (GFLMs), which are widely used for modeling relationships between scalar responses…

Methodology · Statistics 2025-11-14 Feifei Chen , Kaiming Zhang , Yanni Zhang , Hua Liang

We consider the goodness of fit testing problem for stochastic differential equation with small diffiusion coefficient. The basic hypothesis is always simple and it is described by the known trend coefficient. We propose several tests of…

Statistics Theory · Mathematics 2009-03-27 Yury A. Kutoyants

In this paper, we address the problem of testing goodness-of-fit for discrete distributions, where we focus on the geometric distribution. We define new likelihood-based goodness-of-fit tests using the beta-geometric distribution and the…

Statistics Theory · Mathematics 2020-10-09 Rasmus Erlemann , Bo Henry Lindqvist

Logistic regression is widely used to model the propensity score in the analysis of nonignorable missing data. However, goodness-of-fit testing for this propensity score model has received limited attention in the literature. In this paper,…

Methodology · Statistics 2026-04-24 Manli Cheng , Yangjianchen Xu , Qinglong Tian , Pengfei Li
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