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A Comparative Study of Maximum Likelihood Estimation and Bayesian Estimation for Erlang Distribution and Its Applications

In: Statistical Methodologies

Author

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  • Kaisar Ahmad
  • Sheikh Parvaiz Ahmad

Abstract

In this chapter, Erlang distribution is considered. For parameter estimation, maximum likelihood method of estimation, method of moments and Bayesian method of estimation are applied. In Bayesian methodology, different prior distributions are employed under various loss functions to estimate the rate parameter of Erlang distribution. At the end the simulation study is conducted in R-Software to compare these methods by using mean square error with varying sample sizes. Also the real life applications are examined in order to compare the behavior of the data sets in the parametric estimation. The comparison is also done among the different loss functions.

Suggested Citation

  • Kaisar Ahmad & Sheikh Parvaiz Ahmad, 2020. "A Comparative Study of Maximum Likelihood Estimation and Bayesian Estimation for Erlang Distribution and Its Applications," Chapters, in: Jan Peter Hessling (ed.), Statistical Methodologies, IntechOpen.
    • Handle: RePEc:ito:pchaps:176425
    DOI: 10.5772/intechopen.85627
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    More about this item

    Keywords

    Erlang distribution; prior distributions; loss functions; simulation study; applications;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General

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