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Directional and multivariate statist...

Kumar, Somesh.

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Directional and multivariate statistics = a volume in honour of Ashis Sengupta /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Directional and multivariate statistics/ edited by Somesh Kumar ... [et al.].
Reminder of title:	a volume in honour of Ashis Sengupta /
other author:	Kumar, Somesh.
Published:	Singapore :Springer Nature Singapore : : 2025.,
Description:	xxvi, 474 p. :ill., digital ;24 cm.
[NT 15003449]:	Chapter 1 Circular Data Diagnostics in Regression and Time Series Models -- Chapter 2 The Weighting Approach on the Circle -- Chapter 3 Isotonic Regression Estimators for Simultaneous Estimation of Order Restricted Location/Scale Parameters of a Bivariate Distribution: A Unified Study.
Contained By:	Springer Nature eBook
Subject:	Multivariate analysis. -
Online resource:	https://doi.org/10.1007/978-981-96-2004-3
ISBN:	9789819620043

Directional and multivariate statistics = a volume in honour of Ashis Sengupta /
Directional and multivariate statisticsa volume in honour of Ashis Sengupta /[electronic resource] :edited by Somesh Kumar ... [et al.]. - Singapore :Springer Nature Singapore :2025. - xxvi, 474 p. :ill., digital ;24 cm.

Chapter 1 Circular Data Diagnostics in Regression and Time Series Models -- Chapter 2 The Weighting Approach on the Circle -- Chapter 3 Isotonic Regression Estimators for Simultaneous Estimation of Order Restricted Location/Scale Parameters of a Bivariate Distribution: A Unified Study.

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.

ISBN: 9789819620043

Standard No.: 10.1007/978-981-96-2004-3doiSubjects--Topical Terms:

517467
Multivariate analysis.

LC Class. No.: QA278

Dewey Class. No.: 519.535

Directional and multivariate statistics = a volume in honour of Ashis Sengupta /
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505 0 $a Chapter 1 Circular Data Diagnostics in Regression and Time Series Models -- Chapter 2 The Weighting Approach on the Circle -- Chapter 3 Isotonic Regression Estimators for Simultaneous Estimation of Order Restricted Location/Scale Parameters of a Bivariate Distribution: A Unified Study.
520 $a 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.
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