Statistical Concepts for Agricultural Planning
Developing Advanced Forecasting Models for Fertilizer Consumptions in Andhra Pradesh, India
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The basic objective of agricultural planning is to achieve rapid strides in agricultural production coupled with sustainability to meet the needs of ever growing population and to provide them reasonable level of nutritional standards. Efficient planning to use agricultural inputs such as fertilizer in irrigated and rainfed areas are key to get maximum production. This master dissertation discusses descriptive statistics and comparative study of the forecasting models such as Conventional Regression models, Autoregressive Integrated Moving Average (ARIMA) model and Spline Regression model on f...
The basic objective of agricultural planning is to achieve rapid strides in agricultural production coupled with sustainability to meet the needs of ever growing population and to provide them reasonable level of nutritional standards. Efficient planning to use agricultural inputs such as fertilizer in irrigated and rainfed areas are key to get maximum production. This master dissertation discusses descriptive statistics and comparative study of the forecasting models such as Conventional Regression models, Autoregressive Integrated Moving Average (ARIMA) model and Spline Regression model on fertilizer consumptions for irrigated and non-irrigated areas of four districts of Andhra Pradesh. This book of master's dissertation will especially prove a useful reference for researchers to assess agricultural inputs statistically in regional scale.
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