Forecasting based on Markov chain modely | Zendy

V. Ramasubramanian | Zendy; Ravindra Singh Shekhawat | Zendy; Satya P. Singh | Zendy

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Forecasting based on Markov chain modely

Author(s) -

V. Ramasubramanian,

Ravindra Singh Shekhawat,

Satya P. Singh

Publication year - 2019

Publication title -

bhartiya krishi anusandhan patrika

Language(s) - English

Resource type - Journals

eISSN - 0976-4631

pISSN - 0303-3821

DOI - 10.18805/bkap144

Subject(s) - markov chain , outlier , markov model , variable order markov model , econometrics , parametric statistics , mathematics , additive markov chain , markov property , computer science , markov chain monte carlo , markov chain mixing time , statistics , markov process , mathematical optimization , bayesian probability

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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