Some Methods For Estimation Of Small Area Statistics In Agriculture.

      Аннотация: The present book deals with various Small Area estimation techniques for estimating statistics of small geographical area. Application of discriminant function and principal component analysis has been demonstrated to scale down statistics from large level to small level through a linear model established at larger level.Small area level model has also been introduced to improve upon the estimates obtained from the application of discriminant function and principal component analysis.Various methods of cross validation of models fitted with the data have also been described to validate the models used to scale down estimates. Empirical investigation of various methodologies has been carried out with live data particularly on wheat production along with its related covariates for Sultanpur district of Uttar Pradesh, India. The book is quite useful for the policy makers to formulate agricultural development programmes at micro level, i.e. block/ panchyat level in order to enhance the agriculture productivity of the smaller area. The book will also work as reference to the researchers in small area estimation methods.

Ключевые слова: Regression models, Principal Component Analysis, Small area estimation, discriminant function analysis