2023, Vol. 8, Special Issue 4, Part B
Use of Markov chain model for studying disparity in rice yield in the major rice producting districts of West BengalAuthor(s):
Mamata and Dr. D BhattacharyaAbstract:
This paper concentrates in studying the disparity among the districts growing rice by analyzing rice yield data of 1991-92 to 2020-21 for the districts of West Bengal. On the basis thirty years of rice yield data the districts have been classified into three classes (states), namely, highly developed (HD), developed (D) and under developed (UD) by using σ classifier. Next, observing the frequency in the states the transition probability matrix and initial probability vectors are obtained. The steady state probability and expected return time to a particular state are also obtained. Stationary probabilities for different states of each district under study have been used to predict the future movement of the district from one classification to other in terms of rice yield. The model developed for disparity study of a crop is quite general and can be applied to any other related studies. Pages: 78-83 | Views: 62 | Downloads: 9Download Full Article: Click Here
How to cite this article:
Mamata, Dr. D Bhattacharya. Use of Markov chain model for studying disparity in rice yield in the major rice producting districts of West Bengal. Int J Stat Appl Math 2023;8(4S):78-83.