Identifiability of asymmetric circular and cylindrical distributions

08/24/2019
by   Yoichi Miyata, et al.
0

A new method to prove the identifiability of asymmetric circular and cylindrical distributions, which utilizes Teicher's approach, is proposed. We use the simultaneous Diophantine approximations and the trigonometric moments of circular random variables to check some conditions of the proposed method. We prove the identifiability of a general sine-skewed circular distribution including the sine-skewed von Mises and sine-skewed wrapped Cauchy distributions, and a cylindrical distribution combining the sine-skewed von Mises distribution on the circle and the Weibull distribution on the non-negative linear under suitable parameter spaces.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
08/09/2019

Slepian-Bangs formula and Cramer Rao bound for circular and non-circular complex elliptical symmetric distributions

This paper is mainly dedicated to an extension of the Slepian-Bangs form...
research
04/04/2023

Sampling from the surface of a curved torus: A new genesis

The distributions of toroidal data, often viewed as an extension of circ...
research
06/21/2022

Copula bounds for circular data

We propose the extension of Fréchet-Hoeffding copula bounds for circular...
research
02/16/2016

The Multivariate Generalised von Mises distribution: Inference and applications

Circular variables arise in a multitude of data-modelling contexts rangi...
research
07/02/2020

How circular economy and industrial ecology concepts are intertwined? A bibliometric and text mining analysis

Combining new insights from both bibliometric and text mining analyses, ...
research
12/17/2018

Circular Statistics-based low complexity DOA estimation for hearing aid application

The proposed Circular statistics-based Inter-Microphone Phase difference...

Please sign up or login with your details

Forgot password? Click here to reset