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Use of ordinal logistic regression in crop yield forecasting

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Title Use of ordinal logistic regression in crop yield forecasting
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Creator Vandita Kumari
Ranjana Agrawal
 
Subject Ordinal logistic regression
Crop yield forecast
Discriminant function analysis
 
Description Not Available
The performance of ordinal logistic regression and discriminant function analysis has been compared in crop yield forecasting of wheat crop for Kanpur district of Uttar Pradesh. Crop years were divided into two or three groups based on the detrended yield. Crop yield forecast models have been developed using probabilities obtained through ordinal logistic regression along with year as regressors and validated using subsequent years data. In discriminant function approach two types of models were developed, one using scores and another using posterior probabilities. Performance of the models obtained at different weeks was compared using Adj R2, PRESS (Predicted error sum of square), number of misclassifications and forecasts were compared using RMSE (Root Mean Square Error) and MAPE (Mean absolute percentage error) of forecast. Ordinal logistic regression based approach was found to be better than discriminant function analysis approach.
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Date 2017-09-21T10:43:53Z
2017-09-21T10:43:53Z
2016-10-31
 
Type Research Paper
 
Identifier Not Available
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http://krishi.icar.gov.in/jspui/handle/123456789/5301
 
Language English
 
Relation Not Available;
 
Publisher IMD