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Using fixed point characterization, we develop a new goodness of fit test for uniform distribution. We also discuss how the right censored observations can be incorporated in the proposed test procedure. We study the asymptotic properties…

统计方法学 · 统计学 2021-06-14 Sudheesh K. Kattumannil , Sreedevi E. P

In the present paper, we develop a new goodness fit test for gamma distribution using the fixed point characterization. U-Statistic theory is employed to derive the test statistic. We discuss how the right censored observations are…

统计方法学 · 统计学 2021-08-03 Vaisakh K. M. , Sreedevi E. P. , Sudheesh K. Kattumannil

In this paper, a new goodness-of-fit test for a location-scale family based on progressively Type-II censored order statistics is proposed. Using Monte Carlo simulation studies, the present researchers have observed that the proposed test…

统计理论 · 数学 2017-04-25 Hamzeh Torabi , Sayyed Mahmoud Mirjalili , Hossein Nadeb

In this paper, we propose several statistics for testing uniformity under progressive Type-I interval censoring. We obtain the critical points of these statistics and study the power of the proposed tests against a representative set of…

统计理论 · 数学 2017-04-25 H. Nadeb , H. Torabi , G. G. Hamedani

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…

统计方法学 · 统计学 2013-12-12 Christian Goldmann , Bernhard Klar , Simos G. Meintanis

Two new goodness of fit tests for the Pareto type-I distribution for complete and right censored data are proposed using fixed point characterization based on Steins type identity. The asymptotic distributions of the test statistics under…

统计方法学 · 统计学 2024-08-30 Avhad Ganesh Vishnu , Ananya Lahiri , Sudheesh K. Kattumannil

Motivated by applications to goodness of fit testing, the empirical likelihood approach is generalized to allow for the number of constraints to grow with the sample size and for the constraints to use estimated criteria functions. The…

统计理论 · 数学 2013-07-24 Hanxiang Peng , Anton Schick

We develop a new goodness fit test for Rayleigh distribution for complete as well as right censored data. We use U-Statistic theory to derive the test statistic. First we develop a test for complete data and then discuss, how right censored…

统计方法学 · 统计学 2022-08-19 Vaisakh K. M. , Thomas Xavier , Sreedevi E. P

In this paper we test the composite hypothesis that lifetimes follow an exponential distribution based on observed randomly right censored data. Testing this hypothesis is complicated by the presence of this censoring, due to the fact that…

统计方法学 · 统计学 2020-11-10 E. Bothma , J. S. Allison , M. Cockeran , I. J. H. Visagie

A survey of goodness-of-fit and symmetry tests based on the characterization properties of distributions is presented. This approach became popular in recent years. In most cases the test statistics are functionals of $U$-empirical…

统计理论 · 数学 2017-07-07 Ya. Yu. Nikitin

This paper proposes new specification tests for conditional models with discrete responses, which are key to apply efficient maximum likelihood methods, to obtain consistent estimates of partial effects and to get appropriate predictions of…

统计理论 · 数学 2018-02-01 Igor Kheifets , Carlos Velasco

We introduce a kernel-based goodness-of-fit test for censored data, where observations may be missing in random time intervals: a common occurrence in clinical trials and industrial life-testing. The test statistic is straightforward to…

统计方法学 · 统计学 2018-10-11 Tamara Fernández , Arthur Gretton

Analysis of random censored life-time data along with some related stochastic covariables is of great importance in many applied sciences like medical research, population studies and planning etc. The parametric estimation technique…

统计理论 · 数学 2019-05-09 Abhik Ghosh , Ayanendranath Basu

Randomly censored survival data are frequently encountered in applied sciences including biomedical or reliability applications and clinical trial analyses. Testing the significance of statistical hypotheses is crucial in such analyses to…

统计方法学 · 统计学 2019-01-08 Abhik Ghosh , Ayanendranath Basu , Leandro Pardo

We introduce a new statistical test based on the observed spacings of ordered data. The statistic is sensitive to detect non-uniformity in random samples, or short-lived features in event time series. Under some conditions, this new test…

统计方法学 · 统计学 2022-10-27 Philipp Eller , Lolian Shtembari

This paper proposes a goodness of fit test for the generalized Pareto distribution (GPD). Firstly, we provide two characterizations of GPD based on Stein's identity and dynamic survival extropy. These characterizations are used to test GPD…

统计方法学 · 统计学 2025-06-03 Gaurav Kandpal , Nitin Gupta

We develop a systematic, omnibus approach to goodness-of-fit testing for parametric distributional models when the variable of interest is only partially observed due to censoring and/or truncation. In many such designs, tests based on the…

统计方法学 · 统计学 2026-02-10 Juan Carlos Escanciano , Jacobo de Uña-Álvarez

We introduce new consistent and scale-free goodness-of-fit tests for the exponential distribution based on Puri-Rubin characterization. For the construction of test statistics we employ weighted $L^2$ distance between $V$-empirical Laplace…

统计方法学 · 统计学 2023-05-30 Marija Cuparić , Bojana Milošević , Marko Obradović

We consider goodness-of-fit tests for the distribution of the composed error in Stochastic Frontier Models. The proposed test statistic utilizes the characteristic function of the composed error term, and is formulated as a weighted…

统计理论 · 数学 2022-03-01 Simos G. Meintanis , Christos K. Papadimitriou

Computational capability often falls short when confronted with massive data, posing a common challenge in establishing a statistical model or statistical inference method dealing with big data. While subsampling techniques have been…

统计方法学 · 统计学 2024-10-31 Yixiao Ruan , Zan Li , Zhaohui Li , Dennis K. J. Lin , Qingpei Hu , Dan Yu
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