A MARKOV CHAIN ANALYSIS OF DAILY RAINFALL OCCURRENCE AT WESTERN ORISSA OF INDIA

Authors

  • A.K. Mangaraj Department of Statistics, Rajendra Junior College, Bolangir 767002, India
  • L.N. Sahoo Department of Statistics, Utkal University, Bhubaneswar 751004, India
  • M.K. Sukla Department of Statistics, S.V. College, University of Delhi New Delhi 110021

Keywords:

Chi-square test, Dry spell, Goodness of fit, Markov chain probability model, Steady state probability, Transition probability, Weather cycle, Wet spell.

Abstract

This paper makes an attempt to investigate the pattern of occurrence of rainfall such as sequences of wet and dry spells, expected length of such spells, expected length of weather cycle etc. in the western part of Orissa state of India by fitting a 2-state Markov chain probability model to the collected daily rainfall data for a period of 29 years. The key assumption behind reliability of this model is that the occurrence of a wet or a dry day is dependent on the weather condition of the previous day.

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References

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Published

2013-06-03

How to Cite

Mangaraj, A. ., Sahoo, L. ., & Sukla, M. . (2013). A MARKOV CHAIN ANALYSIS OF DAILY RAINFALL OCCURRENCE AT WESTERN ORISSA OF INDIA. Journal of Reliability and Statistical Studies, 6(01), 77–86. Retrieved from https://journals.riverpublishers.com/index.php/JRSS/article/view/21893

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