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Crop Yield Forecasting by Multiple Markov Chain Models and Simulation
2014
Statistics and Applications
unpublished
Markov chain models provide objective pre-harvest forecasts of crop yields with reasonable precisions well in advance aiding timely decisions. However, these models require sizable dataset for them to be stable and reliable. If the dataset is small, the estimated probabilities may not be precise with many zeroes occurring in the transition probability matrices. This will be more so with increase in the order of the Markov chain, because in such cases the number of states increases very rapidly.
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