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Directional statistics for innovative applications: a bicentennial tribute to Florence Nightingale

Contributor(s): Material type: TextTextSeries: Forum for interdisciplinary mathematicsPublication details: Springer 2022 SingaporeDescription: xix, 488 p.: col. ill. Includes referencesISBN:
  • 9789811910432
Subject(s): DDC classification:
  • 519.5 D4
Summary: In commemoration of the bicentennial of the birth of the “lady who gave the rose diagram to us”, this special contributed book pays a statistical tribute to Florence Nightingale. This book presents recent phenomenal developments, both in rigorous theory as well as in emerging methods, for applications in directional statistics, in 25 chapters with contributions from 65 renowned researchers from 25 countries. With the advent of modern techniques in statistical paradigms and statistical machine learning, directional statistics has become an indispensable tool. Ranging from data on circles to that on the spheres, tori and cylinders, this book includes solutions to problems on exploratory data analysis, probability distributions on manifolds, maximum entropy, directional regression analysis, spatio-directional time series, optimal inference, simulation, statistical machine learning with big data, and more, with their innovative applications to emerging real-life problems in astro-statistics, bioinformatics, crystallography, optimal transport, statistical process control, and so on. https://link.springer.com/book/10.1007/978-981-19-1044-9
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Item type Current library Item location Collection Shelving location Call number Status Date due Barcode
Books Vikram Sarabhai Library Rack 28-B / Slot 1411 (0 Floor, East Wing) Non-fiction General Stacks 519.5 D4 (Browse shelf(Opens below)) Available 205180

Table of contents:
1. Quality of Life:
Florence Nightingale, Quality of Life and Statistics

2. Innovative Applications:
Mixture Models for Spherical Data with Applications to Protein Bioinformatics
Statistics of Orientation Relationships in Crystallography
The Statistics of Circular Optimal Transport
Modelling the Movement of Magnetic North
Flexible Circular Modeling: A Case Study of Car Accidents

3. Data Visualization, Simulation and Transformations:
Simulation and Visualization of 3D-Spherical Distributions
Transformations to Improve the Approximation by a von Mises Distribution

4. Distribution Theory and Parametric Inference:
Generalized Skew-Symmetric Circular and Toroidal Distributions
Information Theoretic Results for Stationary Time Series and the Gaussian-Generalized von Mises Time Series
A Circular Distribution Constructed from the Product of Cardioid-Type Densities with (Hyper-) Toroidal Extension
On Some Flexible Models for Circular, Toroidal, and Cylindrical Data
Bivariate Cardioid Distributions
Statistical Inference Using the Three-Parameter Generalized von Mises Distribution and Outlier Detection Method for Asymmetrically Distributed Circular Data

5. Regression Analysis


In commemoration of the bicentennial of the birth of the “lady who gave the rose diagram to us”, this special contributed book pays a statistical tribute to Florence Nightingale. This book presents recent phenomenal developments, both in rigorous theory as well as in emerging methods, for applications in directional statistics, in 25 chapters with contributions from 65 renowned researchers from 25 countries. With the advent of modern techniques in statistical paradigms and statistical machine learning, directional statistics has become an indispensable tool. Ranging from data on circles to that on the spheres, tori and cylinders, this book includes solutions to problems on exploratory data analysis, probability distributions on manifolds, maximum entropy, directional regression analysis, spatio-directional time series, optimal inference, simulation, statistical machine learning with big data, and more, with their innovative applications to emerging real-life problems in astro-statistics, bioinformatics, crystallography, optimal transport, statistical process control, and so on.

https://link.springer.com/book/10.1007/978-981-19-1044-9

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