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Sine-skewed circular distributions are identifiable and have easily-computable trigonometric moments and a simple random number generation algorithm, whereas they are known to have relatively low levels of asymmetry. This study proposes a…

Methodology · Statistics 2024-02-16 Yoichi Miyata , Takayuki Shiohama , Toshihiro Abe

We introduce a novel family of projected distributions on the circle and the sphere, namely the circular and spherical projected Cauchy distributions, as promising alternatives for modelling circular and spherical data. The circular…

Methodology · Statistics 2024-09-12 Michail Tsagris , Omar Alzeley

In this paper, we propose cylindrical distributions obtained by combining the sine-skewed von Mises distribution (circular part) with the Weibull distribution (linear part). This new model, the WeiSSVM, enjoys numerous advantages: simple…

Methodology · Statistics 2016-01-01 Toshihiro Abe , Christophe Ley

The von Mises distribution is one of the most important distribution in statistics to deal with circular data. In this paper we will consider some basic properties and characterizations of the sine skewed von Mises distribution.

Other Statistics · Statistics 2019-02-08 Mohammad Ahsanullah , M. Z. Anis

\cite{tsagris2025a} proposed the generalized circular projected Cauchy (GCPC) distribution, whose special case is the wrapped Cauchy distribution. In this paper we first derive the relationship with the wrapped Cauchy distribution, and then…

Statistics Theory · Mathematics 2026-03-26 Omar Alzeley , Michail Tsagris

In this paper, we propose optimal tests for circular reflective symmetry about a fixed median direction. The distributions against which optimality is achieved are the so-called k-sine-skewed distributions of Umbach and Jammalamadaka…

Methodology · Statistics 2013-03-27 Christophe Ley , Thomas Verdebout

The contribution of this work is the introduction of a multivariate circular-linear (or poly- cylindrical) distribution obtained by combining the projected and the skew-normal. We show the flexibility of our proposal, its property of…

Methodology · Statistics 2017-11-29 Gianluca Mastrantonio

In this note, we investigate the non-identifiability of the multivariate unified skew-normal distribution under permutation of its latent variables. We show that the non-identifiability issue also holds with other parametrizations and…

Statistics Theory · Mathematics 2023-06-23 Kesen Wang , Reinaldo B. Arellano-Valle , Adelchi Azzalini , Marc G. Genton

Motivated by some cutting edge circular data such as from Smart Home technologies and roulette spins from online and casino, we construct some new rich classes of discrete distributions on the circle. We give four new general methods of…

Statistics Theory · Mathematics 2022-05-02 Kanti V. Mardia , Karthik Sriram

In the bioinformatics field, there has been a growing interest in modelling dihedral angles of amino acids by viewing them as data on the torus. This has motivated, over the past years, new proposals of distributions on the bivariate torus.…

Methodology · Statistics 2020-09-01 Jose Ameijeiras-Alonso , Christophe Ley

In this paper we propose a family of multivariate asymmetric distributions over an arbitrary subset of set of real numbers which is defined in terms of the well-known elliptically symmetric distributions. We explore essential properties,…

Methodology · Statistics 2024-09-02 Roberto Vila , Helton Saulo , Leonardo Santos , João Monteiros , Felipe Quintino

Skewness is a common occurrence in statistical applications. In recent years, various distribution families have been proposed to model skewed data by introducing unequal scales based on the median or mode. However, we argue that the point…

Methodology · Statistics 2024-01-10 Yiyuan She , Xiaoqiang Wu , Lizhu Tao , Debajyoti Sinha

The new Sine Skewed Cardioid (ssc) distribution been just introduced and characterized by Ahsanullah (2018). Here, we study the asymptotic properties of its tails by determining its extreme value domain, the characteristic function, the…

We propose a family of four-parameter distributions that contain the K-distribution as special case. The family is derived as a mixture distribution that uses the three-parameter reflected Gamma distribution as parental and the…

Statistics Theory · Mathematics 2021-07-09 Stylianos E. Trevlakis , Nestor D. Chatzidiamantis , George K. Karagiannidis

The family of skew-symmetric distributions is a wide set of probability density functions obtained by combining in a suitable form a few components which are selectable quite freely provided some simple requirements are satisfied. Intense…

Probability · Mathematics 2010-12-22 Adelchi Azzalini , Giuliana Regoli

Laplace distribution is popular in the field of economics and finance. Still, data sets often show a lack of symmetry and a tendency of being bounded from either side of their support. In view of this, we introduce a new family of skew…

Statistics Theory · Mathematics 2024-06-18 Raju. K. Lohot , V. U. Dixit

We introduce a multivariate hidden Markov model to jointly cluster time-series observations with different support, i.e. circular and linear. Relying on the general projected normal distribution, our approach allows for bimodal and/or…

Applications · Statistics 2015-01-27 Gianluca Mastrantonio , Antonello Maruotti , Giovanna Jona Lasinio

We present a Gaussian ensemble of random cyclic matrices on the real field and study their spectral fluctuations. These cyclic matrices are shown to be pseudo-symmetric with respect to generalized parity. We calculate the joint probability…

Mathematical Physics · Physics 2013-02-13 Sudhir R. Jain , Shashi C. L. Srivastava

For the family of multivariate probability distributions variously denoted as unified skew-normal, closed skew-normal and other names, a number of properties are already known, but many others are not, even some basic ones. The present…

Statistics Theory · Mathematics 2020-11-13 Reinaldo B. Arellano-Valle , Adelchi Azzalini

This paper introduces constrained mixtures for continuous distributions, characterized by a mixture of distributions where each distribution has a shape similar to the base distribution and disjoint domains. This new concept is used to…

Machine Learning · Statistics 2015-03-29 Conrado S. Miranda , Fernando J. Von Zuben
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