<p>This book contains select chapters on a range of topics in directional statistics, multivariate statistical inference, financial statistics, statistical machine learning and reliability inference. At the 43rd Annual Convention of the Indian Society for Probability and Statistics (ISPS) held in Prayagraj (formerly Allahabad), Uttar Pradesh, India, from 6–8 February 2024, attribute was paid to Prof. Ashis SenGupta on the occasion of his 70th birthday. He has pioneered research on directional statistics in the modern era in India and enhanced it worldwide and contributed significantly to the advancement of the following topics:</p><ul> <li>Highly flexible distributions on manifolds</li> <li>Statistical machine learning in data science</li> <li>Big data on manifolds</li> <li>Optimal multiparameter, multivariate statistical inference</li> <li>Reliability inference and stress-dependent-strength models</li> <li>Directional statistics for highly volatile financial models</li> <li>Cylindrical, spherical and toroidal regression analysis</li> <li>Innovative applications of emerging real-life directional data</li></ul>

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Directional and Multivariate Statistics

摘要

This book contains select chapters on a range of topics in directional statistics, multivariate statistical inference, financial statistics, statistical machine learning and reliability inference. At the 43rd Annual Convention of the Indian Society for Probability and Statistics (ISPS) held in Prayagraj (formerly Allahabad), Uttar Pradesh, India, from 6–8 February 2024, attribute was paid to Prof. Ashis SenGupta on the occasion of his 70th birthday. He has pioneered research on directional statistics in the modern era in India and enhanced it worldwide and contributed significantly to the advancement of the following topics:

  • Highly flexible distributions on manifolds
  • Statistical machine learning in data science
  • Big data on manifolds
  • Optimal multiparameter, multivariate statistical inference
  • Reliability inference and stress-dependent-strength models
  • Directional statistics for highly volatile financial models
  • Cylindrical, spherical and toroidal regression analysis
  • Innovative applications of emerging real-life directional data