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Abstract
The present study proposes a method to estimate the yield of a crop. The proposed Gaussian quadrature (GQ) method makes it possible to estimate the crop yield from a smaller subsample. Identification of plots and corresponding weights to be assigned to the yield of plots comprising a subsample is done with the help of information about the full sample on certain auxiliary variables relating to biometrical characteristics of the plant. Computational experience reveals that the proposed method leads to about 78% reduction in sample size with absolute percentage error of 2.7%. Performance of the proposed method has been compared with that of random sampling on the basis of the values of average absolute percentage error and standard deviation of yield estimates obtained from 40 samples of comparable size. Interestingly, average absolute percentage error as well as standard deviation is considerably smaller for the GQ estimates than for the random sample estimates. The proposed method is quite general and can be applied for other crops as well-provided information on auxiliary variables relating to yield contributing biometrical characteristics is available.
Acknowledgements
Author is grateful to Dr Ranjana Agarwal, Head, Forecasting Division, Indian Agricultural Statistics Research Institute, New Delhi, and Dr S.D. Sharma, Assistant Director General, Indian Council of Agricultural Research, New Delhi, India, for providing the data. The study was supported by Indian Institute of Management Lucknow, India, in the form of a research grant (No. SM-106). The author gratefully acknowledges the contributive comments of the anonymous referees that considerably improved the quality of the paper.