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:: Volume 15, Issue 1 (9-2021) ::
JSS 2021, 15(1): 39-60 Back to browse issues page
Employing Weighted Operators in Ordered Least Deviations Regression Model
Jalal Chachi * , Alireza Chaji
Abstract:   (2106 Views)
This article introduces a new method to estimate the least absolutes linear regression model's parameters, which considers optimization problems based on the weighted aggregation operators of ordered least absolute deviations. In the optimization problem, weighted aggregation of orderd fitted least absolute deviations provides data analysis to identify the outliers while considering different fitting functions simultaneously in the modeling problem. Accordingly, this approach is not affected by outlier observations and in any problem proportional to the number of potential outliers selects the best model estimator with the optimal break-down point among a set of other candidate estimators. The performance and the goodness-of-fit of the proposed approach are investigated, analyzed and compared in modeling analytical dataset and a real value dataset in hydrology engineering at the presence of outliers. Based on the results of the sensitivity analysis, the properties of unbiasedness and efficiency of the estimators are obtained.
Keywords: Weighted Regression, Ordered Absolutes-Deviations, Breakdown Point, Squared Errors.
Full-Text [PDF 1417 kb]   (978 Downloads)    
Type of Study: Research | Subject: General
Received: 2020/01/29 | Accepted: 2021/09/1 | Published: 2021/03/15
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Chachi J, Chaji A. Employing Weighted Operators in Ordered Least Deviations Regression Model. JSS 2021; 15 (1) :39-60
URL: http://jss.irstat.ir/article-1-694-en.html


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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 15, Issue 1 (9-2021) Back to browse issues page
مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences

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