@inproceedings{9997f47d755e4b15bf2d59c024c67c87,
title = "Robust regression for estimating the burr xii parameters with outliers",
abstract = "The Burr XII distribution offers an even more flexible alternative to the lognormal and the log-logistic distributions. This paper presents a study of the efficiency of using robust regression, M-estimate method, to estimate the parameters of two-parameter Burr XII distribution. Our proposed method will compare with other methods such as unweighted least squares method and maximum likelihood estimation method. The simulated data for complete data and multiple-censoring data with outliers were used to validate the comparison study. Results show that the robust regression method outperforms other methods in most cases in terms of bias and root mean square error.",
keywords = "Burr xii distribution, Least squares estimator, Maximum likelihood estimator, Mestimator, Robust regression estimator",
author = "Cheng, {Yung Fu} and Wang, {Fu Kwun}",
year = "2008",
language = "英语",
isbn = "9781627486828",
series = "38th International Conference on Computers and Industrial Engineering 2008",
pages = "338--347",
booktitle = "38th International Conference on Computers and Industrial Engineering 2008",
note = "38th International Conference on Computers and Industrial Engineering 2008 ; Conference date: 31-10-2008 Through 02-11-2008",
}