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The Use of the Data Transformation Techniques in Estimating the Shape Parameter of the Weibull Distribution for the Wind Speed

The Use of the Data Transformation Techniques in Estimating the Shape Parameter of the Weibull Distribution for the Wind Speed

Yeliz Mert Kantar, Ibrahim Arik
Copyright: © 2014 |Volume: 3 |Issue: 3 |Pages: 14
ISSN: 2160-9500|EISSN: 2160-9543|EISBN13: 9781466654099|DOI: 10.4018/ijeoe.2014070102
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MLA

Kantar, Yeliz Mert, and Ibrahim Arik. "The Use of the Data Transformation Techniques in Estimating the Shape Parameter of the Weibull Distribution for the Wind Speed." IJEOE vol.3, no.3 2014: pp.20-33. http://doi.org/10.4018/ijeoe.2014070102

APA

Kantar, Y. M. & Arik, I. (2014). The Use of the Data Transformation Techniques in Estimating the Shape Parameter of the Weibull Distribution for the Wind Speed. International Journal of Energy Optimization and Engineering (IJEOE), 3(3), 20-33. http://doi.org/10.4018/ijeoe.2014070102

Chicago

Kantar, Yeliz Mert, and Ibrahim Arik. "The Use of the Data Transformation Techniques in Estimating the Shape Parameter of the Weibull Distribution for the Wind Speed," International Journal of Energy Optimization and Engineering (IJEOE) 3, no.3: 20-33. http://doi.org/10.4018/ijeoe.2014070102

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Abstract

In recent years, the Weibull distribution has been commonly used and recommended to model the wind speed. Therefore, many estimators have been proposed to find the best method to estimate the parameters of the Weibull distribution. Particularly, the estimator based on regression procedures with the Weibull probability plot are often used because of its computational simplicity and graphical presentation. However, when the procedure is applied, in many cases heteroscedasticity or non-normality of the error terms may be encountered. One way to handle this problem is using transformation techniques. In this study, the regression estimation based on data transformation is considered to estimate the parameters of the Weibull distribution. The simulation results show that the considered estimator based on the data transformation for the shape parameter of the Weibull distribution provides better performance than least squares estimator in terms of bias and mean square errors for the most of the considered cases.

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