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Copula Bounds for Circular Data
We propose an extension of the Fréchet–Hoeffding copula bounds for circular data. The copula is a powerful tool for describing the dependency of...
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Clustering Circular Data via Finite Mixtures of von Mises Distributions and an Application to Data on Wind Directions
The von Mises distribution, which is also known as the Circular Normal distribution is a well-studied and commonly used distribution for analyzing...
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Spatial Autoregressive Models for Circular Data
A class of autoregressive models for spatial circular data is proposed by assuming that samples of angular measurements are drawn from a multivariate...
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On Nonparametric Density Estimation for Circular Data: An Overview
This paper provides a short review of modern smoothing methods for density and distribution functions dealing with circular data. We highlight the...
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Improving kernel-based nonparametric regression for circular–linear data
We discuss kernel-based nonparametric regression where a predictor has support on a circle and a responder has support on a real line. Nonparametric...
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Families of Discrete Circular Distributions with Some Novel Applications
We give a unified treatment of constructing families of circular discrete distributions. Some of these families are deduced from established...
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An adaptive method for bandwidth selection in circular kernel density estimation
Kernel density estimations of circular data are an effective type of nonparametric estimation. The performance of these estimations depends...
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On Some Flexible Models for Circular, Toroidal, and Cylindrical Data
Some new circular, toroidal, and joint cylindrical models are proposed. Trigonometric moments and random number generation are considered. A family...
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Identifiability of Asymmetric Circular and Cylindrical Distributions
Identifiability of statistical models is a fundamental and essential condition that is required to prove the consistency of maximum likelihood...
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Kernel regression for errors-in-variables problems in the circular domain
We study the problem of estimating a regression function when the predictor and/or the response are circular random variables in the presence of...
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Nonparametric estimation for a functional-circular regression model
Changes on temperature patterns, on a local scale, are perceived by individuals as the most direct indicators of global warming and climate change....
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Modelling Circular Time Series with Applications
Circular time series modelling has posed a big challenge to many researchers due to the nature of observations. This article traces different...
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Detecting Change in the Number of Modes for Circular Data
In this paper, we investigate change-point problems for the number of modes in circular data. We use a mixture of two circular normal distributions...
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Complex Multiplication Model for Circular Regression
In this chapter, we treat circular data as unit complex numbers and model their correlation by multiplying them in the complex plane. We propose a...
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Statistical Inference Using the Three-Parameter Generalized von Mises Distribution and Outlier Detection Method for Asymmetrically Distributed Circular Data
It is well known that circular data are rarely symmetrically distributed; therefore, symmetric distributions such as von Mises and wrapped Cauchy...
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A Two-sample Nonparametric Test for Circular Data– its Exact Distribution and Performance
A nonparametric test labelled ‘Rao Spacing-frequencies test’ is explored and developed for testing whether two circular samples come from the same...
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On the circular correlation coefficients for bivariate von Mises distributions on a torus
This paper studies circular correlations for the bivariate von Mises sine and cosine distributions. These are two simple and appealing models for...
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The Statistics of Circular Optimal Transport
Empirical optimal transport (OT) plans and distances provide effective tools to compare and statistically match probability measures defined on a...
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Generalized Skew-Symmetric Circular and Toroidal Distributions
Existing circular and toroidal distributions are mostly symmetric; however, many datasets possess asymmetric patterns. Due to the increasing need for...
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Automatic data-based bin width selection for rose diagram
A rose diagram is a representation that circularly organizes data with the bin width as the central angle. This diagram is widely used to display and...
