Rainfall Analysis of Guwahati City Using the Method of L-Moments, Tl-Moments & Maximum Likelihood Estimation

Ruhiteswar Choudhury¹ , Tanusree Deb Roy²

1. Dept. of Statistics, Assam University, Silchar, Assam, India.
2. Dept. of Statistics, Assam University, Silchar, Assam, India.

Section:Research Paper, Product Type: Journal-Paper
Vol.10 , Issue.5 , pp.19-25, May-2024

Online published on May 31, 2024

Copyright © Ruhiteswar Choudhury, Tanusree Deb Roy . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
This paper consists of three types of estimation of parameter methods which are namely Maximum Likelihood Estimation (MLE), L-Moments, TL-Moments for estimating parameters of four types of probability distribution including Generalized Extreme Value (GEV), Generalized Pareto (GPA), Generalized Logistic (GLO) & Pearson Type III (PEIII) distribution. Furthermore, Root Mean Square Error (RMSE) values have been calculated to assess the performance of the mentioned distributions for the respective seasons. Finally, 37 years of rainfall data for each month has been analysed, where for winter & Pre-Monsoon season the Pearson Type III distribution is computed as the best fitted probability distribution, for Monsoon and Post-Monsoon season GEV and GPA are found to be the best fitted probability distributions respectively. Interpreting the RMSE values, out of the three kinds of parameter estimation method, L-Moments turns out to be the most efficient method.

Key-Words / Index Term :
Parameter, Generalized Extreme Value, Generalized Logistic, Generalized Pareto, Pearson Type III, Root Mean Square Error.

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