Applications of Regression Techniques (Paperback, 1st ed. 2019)

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.

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Release date:	August 2020
First published:	2019
Authors:	Manoranjan Pal • Premananda Bharati
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	175
Edition:	1st ed. 2019
ISBN-13:	978-981-13-9316-7
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Business & Economics > Economics > Econometrics > General
LSN:	981-13-9316-8
Barcode:	9789811393167

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