| 書目名稱 | Principal Component Regression for Crop Yield Estimation |
| 編輯 | T.M.V Suryanarayana,P. B Mistry |
| 視頻video | http://file.papertrans.cn/756/755295/755295.mp4 |
| 概述 | Includes supplementary material: |
| 叢書名稱 | SpringerBriefs in Applied Sciences and Technology |
| 圖書封面 |  |
| 描述 | This book highlights the estimation of crop yield in CentralGujarat, especially with regard to the development of Multiple RegressionModels and Principal Component Regression (PCR) models using climatologicalparameters as independent variables and crop yield as a dependent variable. Itsubsequently compares the multiple linear regression (MLR) and PCR results, anddiscusses the significance of PCR for crop yield estimation. In this context,the book also covers Principal Component Analysis (PCA), a statistical procedureused to reduce a number of correlated variables into a smaller number ofuncorrelated variables called principal components (PC). This book will behelpful to the students and researchers, starting their works on climate andagriculture, mainly focussing on estimation models. The flow of chapters takesthe readers in a smooth path, in understanding climate and weather and impactof climate change, and gradually proceeds towards downscaling techniques andthen finallytowards development of principal component regression models andapplying the same for the crop yield estimation.. |
| 出版日期 | Book 2016 |
| 關(guān)鍵詞 | Principal Component Regression (PCR); Multiple Linear Regression Models (MLR); Principal Component Ana |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-981-10-0663-0 |
| isbn_softcover | 978-981-10-0662-3 |
| isbn_ebook | 978-981-10-0663-0Series ISSN 2191-530X Series E-ISSN 2191-5318 |
| issn_series | 2191-530X |
| copyright | Springer International Publishing Switzerland 2016 |
|Archiver|手機版|小黑屋|
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