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Principal component regression for crop yield estimation

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Principal component regression for crop yield estimation/ by T.M.V. Suryanarayana, P.B. Mistry.
作者:	Suryanarayana, T.M.V.
其他作者:	Mistry, P.B.
出版者:	Singapore :Springer Singapore : : 2016.,
面頁冊數:	xvii, 67 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
標題:	Crops and climate. -
電子資源:	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:

568689
Crops and climate.

LC Class. No.: S600.5

Dewey Class. No.: 630.2515

Principal component regression for crop yield estimation
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245 1 0 $a Principal component regression for crop yield estimation $h [electronic resource] / $c by T.M.V. Suryanarayana, P.B. Mistry.
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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.
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