Gini Inequality Index: Methods and Applications features original high-quality peer-reviewed chapters prepared by internationally acclaimed researchers.
Gini Inequality Index: Methods and Applications features original high-quality peer-reviewed chapters prepared by internationally acclaimed researchers.
Professor Nitis Mukhopadhyay received PhD degree from Indian Statistical Institute-Calcutta based on a dissertation dated 1975. He is a full professor (since 1985), Department of Statistics, University of Connecticut-Storrs and served as Head of this department during 1987-90. Professor Mukhopadhyay is an Honorary Fellow of the Institute of Applied Statistics Sri Lanka. He is a world-traveler visiting many corners of the globe as an international delegate delivering specially invited Plenary, Keynote, Opening and other major presentations and run workshops on topics including Statistics, Applied Probability, Mathematics, Management Informatics, Econometrics and Teaching. Professor Partha Pratim Sengupta is Professor of Economics, Ex-Head of Department of Humanities and Social Sciences, and Founder Head of Department of Management Studies, National Institute of Technology Durgapur, India. He has teaching experiences of nearly 38 years at UG and PG level and research experience of 24 years. Professor Sengupta obtained the Ph.D. degree in Economics from Jadavpur University, India. To date, twenty one students have been awarded Doctorate degree under his supervision. He has published more than one hundred research papers in reputed national and international level peer reviewed and indexed journals.
Inhaltsangabe
1. Introducing Informal Inequality Measures (IIMs) Constructed from U-statistics of Degree Three or Higher in Analyzing Economic Disparity. 2. The Decomposition of the Gini Index Between and Within Groups: A Key Factor in Gender Studies. 3. A Note on the Decomposition of Health Inequality by Population Subgroups in the Case of Ordinal Variables. 4. The Gini index decomposition and the overlapping between population subgroups. 5. Gini's Mean Difference Based Minimum Risk Point Estimator of Mean. 6. The Gini concentration index for the study of survival. 7. An Axiomatic Analysis of Air Quality Assessment. 8. Sequential Interval and Point Estimation of Gini Index by Controlling Accuracies Relative to the Mean. 9. A Test on Correlation based on Gini's Mean Difference. 10. Multi-group Segregation for Nominal and Ordinal Categorical Data. 11. Exploring Fixed-Accuracy Estimation for Population Gini Inequality Index Under Big Data: A Passage to Practical Distribution-Free Strategies.
1. Introducing Informal Inequality Measures (IIMs) Constructed from U-statistics of Degree Three or Higher in Analyzing Economic Disparity. 2. The Decomposition of the Gini Index Between and Within Groups: A Key Factor in Gender Studies. 3. A Note on the Decomposition of Health Inequality by Population Subgroups in the Case of Ordinal Variables. 4. The Gini index decomposition and the overlapping between population subgroups. 5. Gini's Mean Difference Based Minimum Risk Point Estimator of Mean. 6. The Gini concentration index for the study of survival. 7. An Axiomatic Analysis of Air Quality Assessment. 8. Sequential Interval and Point Estimation of Gini Index by Controlling Accuracies Relative to the Mean. 9. A Test on Correlation based on Gini's Mean Difference. 10. Multi-group Segregation for Nominal and Ordinal Categorical Data. 11. Exploring Fixed-Accuracy Estimation for Population Gini Inequality Index Under Big Data: A Passage to Practical Distribution-Free Strategies.
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