2019•Bhartiya Krishi Anusandhan PatrikaOpen access

Forecasting based on Markov chain modely

V. Ramasubramanian, Ravindra Singh Shekhawat, SATYA PRAKASH SINGH

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Abstract

In this paper, we try to forecast crop yield by the probability model based on Markov Chain theory, which overcomes some of the drawbacks of the regression model. Markov Chain models are not constrained by a parametric assumption and are robust against outliers and extreme values. Here, multiple order Markov chain were utilized.

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What this paper is about

In this paper, we try to forecast crop yield by the probability model based on Markov Chain theory, which overcomes some of the drawbacks of the regression model. Markov Chain models are not constrained by a parametric assumption and are robust against outliers and extreme values. Here, multiple order Markov chain were utilized.

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Available abstract

In this paper, we try to forecast crop yield by the probability model based on Markov Chain theory, which overcomes some of the drawbacks of the regression model. Markov Chain models are not constrained by a parametric assumption and are robust against outliers and extreme values. Here, multiple order Markov chain were utilized.

Key concepts: Markov chain, Outlier, Markov model, Variable-order Markov model, Econometrics, Parametric statistics, Mathematics, Additive Markov chain

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