Markov chain is the sub topic in the stochastic process. you have to understand the probability distribution and matrix. here data are arranged in terms of matrix following states/steps. You can arrange in terms of column (crop 1, 2,3,4) and in row wise arranged (area, production, yield) . this will constitute the so called matrix . what next computing the probability in terms of rows and colum establishing the transition matrix whose
Sorry, but you ask a strange question. Why did you chose Markov chains? Why not factor analysis, design of experiments, time series, stationary processes and so on ? You should first to define for yourselves what do you want obtain from the data, what is the goal of your study.Ilya
Actually Sir, I was trying to learn the Markov Chains and was thinking if I could apply the same for the Availble data on Area and production of principle crops to identify the transition process in the state agriculture in last 35 years.