2013
DOI: 10.22237/jmasm/1383279420
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Comparison of Parameters of Lognormal Distribution Based On the Classical and Posterior Estimates

Abstract: Lognormal distribution is widely used in scientific field, such as agricultural, entomological, biology etc. If a variable can be thought as the multiplicative product of some positive independent random variables, then it could be modelled as lognormal. In this study, maximum likelihood estimates and posterior estimates of the parameters of lognormal distribution are obtained and using these estimates we calculate the point estimates of mean and variance for making comparisons.

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Cited by 3 publications
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“…There are many techniques to estimate the distribution parameters, namely the method of moments, percentiles and maximum likelihood estimation (MLE) [Georgopoulos and Seinfeld (1982)] and Bayesian method of estimation [Sultan and Ahmad (2013)]. The method of moments was more widely used whereas the method of maximum likelihood provides the best estimate of the parameters [Mage and Ott (1984)].…”
Section: A Multidisciplinary Research Journalmentioning
confidence: 99%
“…There are many techniques to estimate the distribution parameters, namely the method of moments, percentiles and maximum likelihood estimation (MLE) [Georgopoulos and Seinfeld (1982)] and Bayesian method of estimation [Sultan and Ahmad (2013)]. The method of moments was more widely used whereas the method of maximum likelihood provides the best estimate of the parameters [Mage and Ott (1984)].…”
Section: A Multidisciplinary Research Journalmentioning
confidence: 99%