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Mathematical and Computational Applications is published by MDPI from Volume 21 Issue 1 (2016). Articles in this Issue were published by another publisher in Open Access under a CC-BY (or CC-BY-NC-ND) licence. Articles are hosted by MDPI on mdpi.com as a courtesy and upon agreement with the previous journal publisher.
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Math. Comput. Appl. 2012, 17(1), 39-47; https://doi.org/10.3390/mca17010039

Computation Approaches for Parameter Estimation of Weibull Distribution

Department of Applied Statistics, National Taichung Institute of Technology, Taichung 404, R.O.C, Taiwan
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Published: 1 April 2012
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Abstract

This paper examines the estimation comparison of two methods for Weibull parameters, one is the maximum likelihood method and the other is the least squares method. A numerical simulation study is carried out to understand performance of the two methods. Based on sample root mean square errors, we make a comparison between the two computation approaches. We find that the least squares method significantly outperforms the maximum likelihood when the sample size is small.
Keywords: Weibull distribution; Maximum likelihood method; Least squares method; Sample root mean square error; Simulation Weibull distribution; Maximum likelihood method; Least squares method; Sample root mean square error; Simulation
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).
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Chu, Y.-K.; Ke, J.-C. Computation Approaches for Parameter Estimation of Weibull Distribution. Math. Comput. Appl. 2012, 17, 39-47.

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