A comparative study for the location and scale parameters of the Weibull distribution with given shape parameter
Abstract
Nine parametric estimators of the location and scale parameters of a two-parameter Weibull distribution are compared in terms of their bias and efficiency in a simulation study. The estimators considered are the maximum likelihood estimators (MLE), moment estimators (ME), generalized spacing estimators (GSE), modified maximum likelihood estimators I (MMLE-I), modified maximum likelihood estimators II (MMLE-II), Tiku's modified maximum likelihood estimators (TMMLE), least-squares estimators (LSE), weighted least-squares estimators (WLSE) and percentile estimators (PCE). The aim of the comparisons is to identify the most efficient estimators among these nine estimators for different shape parameters and sample sizes
Source
Computers & GeosciencesVolume
34Issue
12Collections
- Makale Koleksiyonu [129]
- Scopus İndeksli Yayınlar Koleksiyonu [8325]
- WoS İndeksli Yayınlar Koleksiyonu [7605]
Related items
Showing items related by title, author, creator and subject.
-
Estimating variances inweighted least-squares estimation of distributional parameters
Mert Kantar, Yeliz (Association for Scientific Research, 2016)Many estimation methods have been proposed for the parameters of statistical distribution. The least squares estimation method, based on a regression model or probability plot, is frequently used by practitioners since its ... -
Evaluation of robust estimation methods in estimating weibull parameters for wind energy application
Arık, I.; Mert Kantar, Yeliz; Usta, İlhan; Yenilmez, İsmail (Association for Computing Machinery, 2015)Two-parameter Weibull distribution has been widely-used reference distribution in wind energy studies and thus its parameter estimation methods have been well-studied in the literature. However, the literature have generally ... -
Robust ridge and robust Liu estimator for regression based on the LTS estimator
Kan Kılınç, Betül; Alpu, Özlem; Yazıcı, Berna (Taylor & Francis LTD, 2013)In the multiple linear regression analysis, the ridge regression estimator and the Liu estimator are often used to address multicollinearity. Besides multicollinearity, outliers are also a problem in the multiple linear ...