Estimation of Parameters in Erlang Distribution using Prior Information
B. Bhaskara Rama Sarma1, V. Vasanta Kumar2, S.V.N.L. Lalitha3
1B. Bhaskara Rama Sarma, Research Scholar, Department of Mathematics, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, Andhra Pradesh 522502, India.
2V. Vasanta Kumar, Professor, Department of Mathematics, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, Andhra Pradesh 522502, India.
3S.V.N.L. Lalitha, Professor, Department of EEE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, Andhra Pradesh 522502, India.
Manuscript received on 05 March 2019 | Revised Manuscript received on 11 March 2019 | Manuscript published on 30 July 2019 | PP: 4969-4971 | Volume-8 Issue-2, July 2019 | Retrieval Number: B1072078219/19©BEIESP | DOI: 10.35940/ijrte.B1072.078219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper focuses on the estimation of parameters of an Erlang density using known Coefficients of variation and Kurtosis of the population basing on past experience and a simple random sample of size 𝒏 from the population. Estimators using Searle D.T approach are proposed and their bias 𝑩(𝑻) and mean squared error 𝑴(𝑻) are calculated. The relative efficiency of 𝑻 over conventional estimator 𝒙 is also tabulated for various sample sizes and various C.V values, Kurtosis values. The proposed estimators are observed to be more efficient than 𝒙 under the conditions established.
Subject Classification: AMS 62J13
Key Words: Erlang Density, Coefficient of Variation, Coefficient of Kurtosis, Relative Efficiency, Bias, Mean squared error
Scope of the Article: Information Retrieval