Verma G and Pandey KK
Under this investigation we studied about minimization of weekly data through stratification and Simple Randon Sample technique. Individual effect of weather parameters has been considered under the study. Forecasting model developed on two statistical technique i.e. Stepwise Regression Analysis (Forward Method) technique and Discriminat Function Analysis technique. Both the techniques are found very suitable for the district wise and zone level pre-harvest forecast for the pigeonpea crop on Chhattisgarh. Models fitted with the Stepwise Regression Analysis on 35 variables and Time Trend (T) for Zone. The developed model is showing best fit on the basis of very high value of significance and maximum R2 (84%) for the plain Zone, highly significant at 0.1% level of significance and models fitted with DFA then 2 Discriminant score (ds1 and ds2) and Time Trend (T) the models found highly significant and R2 value 69% for plain zone for Pigeonpea crop. The developed model has been validated by the error parameters viz. Minimum MAE, Minimum MSE, Minimum RMSE, Minimum PE and Minimum PD along with maximum R2. These developed models are useful to farmers of Chhattisgarh to decide their future prospects and possible course of action in advance. This was very challenging task for the researchers to develop a precise & accurate and best fit model for the future forecast. May this study will clear the fog through new methodology and also will create the new way on the direction of forecast.
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