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Directional Statistics for Innovative Applications

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Cover of 'Directional Statistics for Innovative Applications'

Table of Contents

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    Book Overview
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    Chapter 1 Florence Nightingale, Quality of Life and Statistics
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    Chapter 2 Mixture Models for Spherical Data with Applications to Protein Bioinformatics
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    Chapter 4 The Statistics of Circular Optimal Transport
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    Chapter 5 Modelling the Movement of Magnetic North
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    Chapter 6 Flexible Circular Modeling: A Case Study of Car Accidents
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    Chapter 7 Simulation and Visualization of 3D-Spherical Distributions
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    Chapter 8 Transformations to Improve the Approximation by a von Mises Distribution
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    Chapter 9 Generalized Skew-Symmetric Circular and Toroidal Distributions
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    Chapter 10 Information Theoretic Results for Stationary Time Series and the Gaussian-Generalized von Mises Time Series
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    Chapter 11 A Circular Distribution Constructed from the Product of Cardioid-Type Densities with (Hyper-) Toroidal Extension
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    Chapter 12 On Some Flexible Models for Circular, Toroidal, and Cylindrical Data
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    Chapter 13 Bivariate Cardioid Distributions
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    Chapter 14 Statistical Inference Using the Three-Parameter Generalized von Mises Distribution and Outlier Detection Method for Asymmetrically Distributed Circular Data
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    Chapter 15 Modeling Wind Direction Using von Mises Regression on Wind Speed
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    Chapter 16 Spatial Autoregressive Models for Circular Data
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    Chapter 17 Complex Multiplication Model for Circular Regression
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    Chapter 18 Regression Models for Directional Variables
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    Chapter 19 On Nonparametric Density Estimation for Circular Data: An Overview
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    Chapter 20 On Weighted Sign Tests for Rotational Symmetry on Hyperspheres
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    Chapter 21 Long-Range Dependence in Directional Data
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    Chapter 22 Modelling Circular Time Series with Applications
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    Chapter 23 Statistical Process Control on the Circle: A Review and Some New Results
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    Chapter 24 Angular-Angular and Linear-Angular Regression Using ANN
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    Chapter 25 Wind Speed and Wind Direction Prediction: An Implementation of a Deep Learning Algorithm Enriched by SWT and Circular PCA
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Title
Directional Statistics for Innovative Applications
Published by
Springer Nature Singapore, June 2022
DOI 10.1007/978-981-19-1044-9
ISBNs
978-9-81-191043-2, 978-9-81-191044-9
Editors

SenGupta, Ashis, Arnold, Barry C.

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