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Related papers: A likelihood ratio test for circular multimodality

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In this paper we investigate the asymptotic distribution of likelihood ratio tests in models with several groups, when the number of groups converges with the dimension and sample size to infinity. We derive central limit theorems for the…

Statistics Theory · Mathematics 2019-07-17 Holger Dette , Nina Dörnemann

The identification of peaks or maxima in probability densities, by mode testing or bump hunting, has become an important problem in applied fields. This task has been approached in the statistical literature from different perspectives,…

Methodology · Statistics 2020-09-01 Jose Ameijeiras-Alonso , Rosa M. Crujeiras , Alberto Rodríguez-Casal

We study a likelihood ratio test for the location of the mode of a log-concave density. Our test is based on comparison of the log-likelihoods corresponding to the unconstrained maximum likelihood estimator of a log-concave density and the…

Statistics Theory · Mathematics 2018-06-05 Charles R. Doss , Jon A. Wellner

In this paper, we show that the likelihood-ratio measure (a) is invariant with respect to dominating sigma-finite measures, (b) satisfies logical consequences which are not satisfied by standard $p$-values, (c) respects frequentist…

Methodology · Statistics 2021-04-07 Alexandre G. Patriota

We investigate the likelihood ratio test for a large block-diagonal covariance matrix with an increasing number of blocks under the null hypothesis. While so far the likelihood ratio statistic has only been studied for normal populations,…

Statistics Theory · Mathematics 2024-08-01 Nina Dörnemann

Fern\'andez-Dur\'an (2004) developed a family of circular distributions based on nonnegative trigonometric sums (NNTS) which is flexible for modeling datasets exhibiting multimodality and asymmetry. Many datasets involving angles in the…

Methodology · Statistics 2025-01-10 Juan José Fernández-Durán , María Mercedes Gregorio-Domínguez

Inference based on the penalized density ratio model is proposed and studied. The model under consideration is specified by assuming that the log--likelihood function of two unknown densities is of some parametric form. The model has been…

Statistics Theory · Mathematics 2008-07-17 Konstantinos Fokianos

Regression models, where the response variable is circular, are common in areas such as biology, geology and meteorology. A typical model assumes that the conditional distribution of the response follows a von-Mises distribution. However,…

Methodology · Statistics 2026-01-12 Sphiwe B. Skhosana , Najmeh Nakhaei Rad

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

Multimodal regression estimation methods are introduced for regression models involving circular response and/or covariate. The regression estimators are based on the maximization of the conditional densities of the response variable over…

Methodology · Statistics 2024-01-10 María Alonso-Pena , Rosa M. Crujeiras

Triangular distributions are a well-known class of distributions that are often used as an elementary example of a probability model. Maximum likelihood estimation of the mode parameter of the triangular distribution over the unit interval…

Other Statistics · Statistics 2016-11-08 Hien D Nguyen , Geoffrey J McLachlan

In this paper, we develop modified versions of the likelihood ratio test for multivariate heteroskedastic errors-in-variables regression models. The error terms are allowed to follow a multivariate distribution in the elliptical class of…

Statistics Theory · Mathematics 2013-03-18 Tatiane F. N. Melo , Silvia L. P. Ferrari , Alexandre G. Patriota

In this work, we derive some novel properties of the bimodal normal distribution. Some of its mathematical properties are examined. We provide a formal proof for the bimodality and assess identifiability. We then discuss the maximum…

Statistics Theory · Mathematics 2021-06-02 Roberto Vila , Helton Saulo , Jamer Roldan

A new plug-in rule procedure for bandwidth selection in kernel circular density estimation is introduced. The performance of this proposal is checked throughout a simulation study considering a variety of circular distributions exhibiting…

Methodology · Statistics 2012-02-29 M. Oliveira , R. M. Crujeiras , A. Rodríguez-Casal

The field of property testing of probability distributions, or distribution testing, aims to provide fast and (most likely) correct answers to questions pertaining to specific aspects of very large datasets. In this work, we consider a…

Data Structures and Algorithms · Computer Science 2015-04-27 Clément L. Canonne

This article describes a method for using optimization to derive efficient independent transition functions for Markov chain Monte Carlo simulations. Our interest is in sampling from a posterior density $\pi(x)$ for problems in which the…

Computation · Statistics 2022-06-03 Dean S. Oliver

Multi-parameter one-sided hypothesis test problems arise naturally in many applications. We are particularly interested in effective tests for monitoring multiple quality indices in forestry products. Our search reveals that there are many…

Statistics Theory · Mathematics 2017-03-16 Guangyu Zhu , Jiahua Chen

We develop a likelihood methodology which can be used to search for evidence of burst repetition in the BATSE catalog, and to study the properties of the repetition signal. We use a simplified model of burst repetition in which a number…

Astrophysics · Physics 2009-10-28 Carlo Graziani , Donald Q. Lamb

A variety of statistics based on sample spacings has been studied in the literature for testing goodness-of-fit to parametric distributions. To test the goodness-of-fit to a nonparametric class of univariate shape-constrained densities,…

Statistics Theory · Mathematics 2024-10-28 Kwun Chuen Gary Chan , Hok Kan Ling , Chuan-Fa Tang , Sheung Chi Phillip Yam

This is an up-to-date introduction to, and overview of, marginal likelihood computation for model selection and hypothesis testing. Computing normalizing constants of probability models (or ratio of constants) is a fundamental issue in many…

Computation · Statistics 2023-02-13 Fernando Llorente , Luca Martino , David Delgado , Javier Lopez-Santiago
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