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Principal component regression for c...

Suryanarayana, T.M.V.

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Principal component regression for crop yield estimation

Record Type:	Electronic resources : Monograph/item
Title/Author:	Principal component regression for crop yield estimation/ by T.M.V. Suryanarayana, P.B. Mistry.
Author:	Suryanarayana, T.M.V.
other author:	Mistry, P.B.
Published:	Singapore :Springer Singapore : : 2016.,
Description:	xvii, 67 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- Principal Component Analysis In Transfer Function -- Review of Litrrature -- Study Area and Data Collection -- Methodology -- Conclusions.
Contained By:	Springer eBooks
Subject:	Crops and climate. -
Online resource:	http://dx.doi.org/10.1007/978-981-10-0663-0
ISBN:	9789811006630

Principal component regression for crop yield estimation
Suryanarayana, T.M.V.

Principal component regression for crop yield estimation[electronic resource] /by T.M.V. Suryanarayana, P.B. Mistry. - Singapore :Springer Singapore :2016. - xvii, 67 p. :ill., digital ;24 cm. - SpringerBriefs in applied sciences and technology,2191-530X. - SpringerBriefs in applied sciences and technology..

Introduction -- Principal Component Analysis In Transfer Function -- Review of Litrrature -- Study Area and Data Collection -- Methodology -- Conclusions.

This book highlights the estimation of crop yield in Central Gujarat, especially with regard to the development of Multiple Regression Models and Principal Component Regression (PCR) models using climatological parameters as independent variables and crop yield as a dependent variable. It subsequently compares the multiple linear regression (MLR) and PCR results, and discusses the significance of PCR for crop yield estimation. In this context, the book also covers Principal Component Analysis (PCA), a statistical procedure used to reduce a number of correlated variables into a smaller number of uncorrelated variables called principal components (PC) This book will be helpful to the students and researchers, starting their works on climate and agriculture, mainly focussing on estimation models. The flow of chapters takes the readers in a smooth path, in understanding climate and weather and impact of climate change, and gradually proceeds towards downscaling techniques and then finally towards development of principal component regression models and applying the same for the crop yield estimation.

ISBN: 9789811006630

Standard No.: 10.1007/978-981-10-0663-0doiSubjects--Topical Terms:

535328
Crops and climate.

LC Class. No.: S600.5

Dewey Class. No.: 630.2515

Principal component regression for crop yield estimation
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100 1 $a Suryanarayana, T.M.V. $3 2186825
245 1 0 $a Principal component regression for crop yield estimation $h [electronic resource] / $c by T.M.V. Suryanarayana, P.B. Mistry.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2016.
300 $a xvii, 67 p. : $b ill., digital ; $c 24 cm.
490 1 $a SpringerBriefs in applied sciences and technology, $x 2191-530X
505 0 $a Introduction -- Principal Component Analysis In Transfer Function -- Review of Litrrature -- Study Area and Data Collection -- Methodology -- Conclusions.
520 $a This book highlights the estimation of crop yield in Central Gujarat, especially with regard to the development of Multiple Regression Models and Principal Component Regression (PCR) models using climatological parameters as independent variables and crop yield as a dependent variable. It subsequently compares the multiple linear regression (MLR) and PCR results, and discusses the significance of PCR for crop yield estimation. In this context, the book also covers Principal Component Analysis (PCA), a statistical procedure used to reduce a number of correlated variables into a smaller number of uncorrelated variables called principal components (PC) This book will be helpful to the students and researchers, starting their works on climate and agriculture, mainly focussing on estimation models. The flow of chapters takes the readers in a smooth path, in understanding climate and weather and impact of climate change, and gradually proceeds towards downscaling techniques and then finally towards development of principal component regression models and applying the same for the crop yield estimation.
650 0 $a Crops and climate. $3 535328
650 0 $a Climatic changes. $3 535326
650 1 4 $a Engineering. $3 586835
650 2 4 $a Appl.Mathematics/Computational Methods of Engineering. $3 890892
650 2 4 $a Climate Change/Climate Change Impacts. $3 2036591
650 2 4 $a Statistical Theory and Methods. $3 891074
650 2 4 $a Math. Appl. in Environmental Science. $3 891071
650 2 4 $a Agriculture. $3 518588
650 2 4 $a Water Policy/Water Governance/Water Management. $3 2054608
700 1 $a Mistry, P.B. $3 2186826
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
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950 $a Engineering (Springer-11647)