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Title
Applications of regression techniques / Manoranjan Pal, Premananda Bharati.
ISBN
9789811393143 (electronic book)
9811393141 (electronic book)
9811393133
9789811393136
Published
Singapore : Springer, [2019]
Language
English
Description
1 online resource
Other Standard Identifiers
10.1007/978-981-13-9
Call Number
QA278.2 .P35 2019
Dewey Decimal Classification
519.5/36
Summary
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.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Source of Description
Description based on online resource; title from digital title page (viewed on August 26, 2019).
Available in Other Form
Print version: 9789811393136
Chapter 1: Introduction to Regression Analysis and an overview of the techniques used in the book
Chapter 2: Regression Decomposition Technique towards Finding Intra-Household Gender Bias of Calorie Consumption
Chapter 3: Estimation of Poverty Rates by Calorie Decomposition Method
Chapter 4: Estimating Calorie-Poverty Rates through Regression
Chapter 5: Contribution of Regressors: A Set Theoretic Approach
Chapter 6: Estimation of Hidden Markov Chain through Regression
Chapter 7: Finding Geometric Mean and Aggregate Growth Rate through regression
Chapter 8: Summary and Discussions.
