 M-estimator for estimating the Burr type III parameters with outliersFu-Kwun Wang and Chih-Wen Lee Mathematics and Computers in Simulation (MATCOM), 2014, vol. 105, issue C, 144-159 Abstract: The Burr type III distribution allows a wider region for the skewness and kurtosis plane, which covers several distributions including: the log-logistic, the Weibull and the Burr type XII distributions. However, outliers may occur in the data set. The robust regression method has been successfully used to diminish the effect of outliers on statistical inference. This paper presents an M-estimator based on the quantile function to estimate the Burr type III parameters for complete data with outliers. We showed that all regularity conditions are satisfied for the normal approximation of the Burr type III distribution using the M-estimator. Thus, the confidence intervals for all parameters can be obtained. The simulation results showed that the M-estimator generally outperforms the maximum likelihood and least squares methods regarding bias, root mean square errors and a number of quantile values. One real example and one simulated data example are used to demonstrate the performance of our proposed method. Keywords: Burr type III distribution; Least squares; Maximum likelihood; M-estimator; Outliers (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:105:y:2014:i:c:p:144-159 DOI: 10.1016/j.matcom.2014.05.010 Access Statistics for this article Mathematics and Computers in Simulation (MATCOM) is currently edited by Robert Beauwens More articles in Mathematics and Computers in Simulation (MATCOM) from Elsevier |
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