國立虎尾科技大學 |

Applications of regression techniques

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Applications of regression techniques/ by Manoranjan Pal, Premananda Bharati.
Author:	Pal, Manoranjan.
other author:	Bharati, Premananda.
Published:	Singapore :Springer Singapore : : 2019.,
Description:	xi, 175 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
Subject:	Regression analysis. -
Online resource:	https://doi.org/10.1007/978-981-13-9314-3
ISBN:	9789811393143

Applications of regression techniques
Pal, Manoranjan.

Applications of regression techniques[electronic resource] /by Manoranjan Pal, Premananda Bharati. - Singapore :Springer Singapore :2019. - xi, 175 p. :ill., digital ;24 cm.

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.

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.

ISBN: 9789811393143

Standard No.: 10.1007/978-981-13-9314-3doiSubjects--Topical Terms:

569541
Regression analysis.

LC Class. No.: QA278.2 / .P356 2019

Dewey Class. No.: 519.536

Applications of regression techniques
LDR:02746nam a2200337 a 4500 001 941994
003 DE-He213
005 20191206131334.0
006 m d
007 cr nn 008maaau
008 200417s2019 si s 0 eng d
020 $a 9789811393143 $q (electronic bk.)
020 $a 9789811393136 $q (paper)
024 7 $a 10.1007/978-981-13-9314-3 $2 doi
035 $a 978-981-13-9314-3
040 $a GP $c GP
041 0 $a eng
050 4 $a QA278.2 $b .P356 2019
072 7 $a PBT $2 bicssc
072 7 $a BUS061000 $2 bisacsh
072 7 $a PBT $2 thema
072 7 $a K $2 thema
082 0 4 $a 519.536 $2 23
090 $a QA278.2 $b .P153 2019
100 1 $a Pal, Manoranjan. $3 1197223
245 1 0 $a Applications of regression techniques $h [electronic resource] / $c by Manoranjan Pal, Premananda Bharati.
260 $a Singapore : $c 2019. $b Springer Singapore : $b Imprint: Springer,
300 $a xi, 175 p. : $b ill., digital ; $c 24 cm.
505 0 $a 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.
520 $a 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.
650 0 $a Regression analysis. $3 569541
650 1 4 $a Statistics for Business, Management, Economics, Finance, Insurance. $3 1211158
650 2 4 $a Econometrics. $3 556981
650 2 4 $a Statistical Theory and Methods. $3 671396
700 1 $a Bharati, Premananda. $3 1197224
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer eBooks
856 4 0 $u https://doi.org/10.1007/978-981-13-9314-3
950 $a Mathematics and Statistics (Springer-11649)