A Markov chain model for daily rainfall occurrences  at east Thanjavur district

Authors

  • M. THIYAGARAJAN
  • RAMA DOSS
  • RAMA RAJ

DOI:

https://doi.org/10.54302/mausam.v46i4.3305

Abstract

 The occurrences and non-occurrences of the rainfall can be described by a two-state Markov chain. A dry date is denoted by state 0 and wet date is denoted by state 1. We have taken the sample which follows a Poisson process with known parameter. Using this Poisson sample we have given a new approach to affect statistical inference for the law of the Markov chain and state estimation concerning un-observed past values or not yet observed future values. The paper aims at comparing the earlier fit of the data with the new approach.

 

 

 

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Published

1995-10-01

Issue

Vol. 46 No. 4 (1995): MAUSAM

Section

Shorter Contribution

Categories

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How to Cite

[1]
“A Markov chain model for daily rainfall occurrences  at east Thanjavur district”, MAUSAM, vol. 46, no. 4, pp. 383–388, Oct. 1995, doi: 10.54302/mausam.v46i4.3305.