Applications of Regression Techniques (PDF)
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This book discusses the need to carefully and prudently apply various regression techniques in order to obtain the full benefits. It also describes some of the techniques developed and used by the authors, presenting their innovative ideas regarding the formulation and estimation of regression decomposition models, hidden Markov chain, and the contribution of regressors in the set-theoretic approach, calorie poverty rate, and aggregate growth rate. Each of these techniques has applications that address a number of unanswered questions; for example, regression decomposition techniques reveal intra-household gender inequalities of consumption, intra-household allocation of resources and adult equivalent scales, while Hidden Markov chain models can forecast the results of future elections. Most of these procedures are presented using real-world data, and the techniques can be applied in other similar situations. Showing how difficult questions can be answered by developing simple models with simple interpretation of parameters, the book is a valuable resource for students and researchers in the field of model building.
Premananda Bharati, former Professor at the Indian Statistical Institute, obtained his Ph.D. in Anthropology from the University of Calcutta. He has extensive teaching experience, including teaching courses in Anthropology to graduate and postgraduate students at the Indian Statistical Institute and other universities, including institutes abroad. He is an examiner and paper setter in Anthropology for various universities, and reviews papers for a number of journals. He has published more than 100 papers in reputed national and international journals. His research interests include nutrition and health, anthropometry, empowerment of women and tribal communities.
- Autoren: Manoranjan Pal , Premananda Bharati
- 2019, 1st ed. 2019, 175 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 9811393141
- ISBN-13: 9789811393143
- Erscheinungsdatum: 18.07.2019
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