Comparing Parameter Estimates Obtained by Simulation Study and Real Life Data from the Two-Parameter Gamma Model
International Journal of Statistical Distributions and Applications
Volume 3, Issue 2, June 2017, Pages: 13-17
Received: Aug. 27, 2016;
Accepted: Nov. 30, 2016;
Published: May 6, 2017
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A. M. Yahaya, Department of Mathematics and Statistics, University of Maiduguri, Maiduguri, Nigeria
N. P. Dibal, Department of Mathematics and Statistics, University of Maiduguri, Maiduguri, Nigeria
H. R. Bakari, Department of Mathematics and Statistics, University of Maiduguri, Maiduguri, Nigeria
The aim of this study was to employ Maximum Likelihood (MLE) jointly with a numerical Method (Newton Raphson method) to obtain parameter estimates from the two-parameter Gamma model. The profile likelihood of the two-parameter Gamma model was also put into consideration. The methods were demonstrated using simulation studies and real life data considering data sets generated by R statistical software for different sample sizes. Standard errors were computed and 5 % Wald-confidence interval was constructed for the estimates of the model. The result of the study shows that Maximum Likelihood Estimation (MLE) jointly with Newton Raphson method was more efficient for estimating parameters of the Gamma model in simulation study than real life data. The study recommends that parameter estimates from the two-parameter Gamma model should be obtained by employing Maximum Likelihood Estimation jointly with Newton Raphson Method.
A. M. Yahaya,
N. P. Dibal,
H. R. Bakari,
Comparing Parameter Estimates Obtained by Simulation Study and Real Life Data from the Two-Parameter Gamma Model, International Journal of Statistical Distributions and Applications.
Vol. 3, No. 2,
2017, pp. 13-17.
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