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:: Volume 28, Issue 2 (3-2024) ::
Andishe 2024, 28(2): 1-9 Back to browse issues page
Regression Modeling for Linguistic Data under Fuzzy Random Errors
Maryam Maleki , Hamid Reza Nili-Sani * , M.GH. Akari
Abstract:   (62 Views)
In this article, logistic regression models are studied in which the response variables are two (or multiple) values and the explanatory variables (predictor or independent) are ordinary variables, but the errors have a vagueness nature in addition to being random. Based on this, we formulate the proposed model and determine the estimation of the coefficients for a case with only one explanatory variable using the method of least squares. In the end, we explain the results with an example.
Article number: 1
Keywords: Logistic regression, Fuzzy random variables, Fuzzy Linguistic random variables
Full-Text [PDF 252 kb]   (66 Downloads)    
Type of Study: Research | Subject: General
Received: 2023/12/10 | Accepted: 2024/09/29 | Published: 2025/01/17
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Maleki M, Nili-Sani H R, Akari M. Regression Modeling for Linguistic Data under Fuzzy Random Errors. Andishe 2024; 28 (2) : 1
URL: http://andisheyeamari.irstat.ir/article-1-943-en.html


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Volume 28, Issue 2 (3-2024) Back to browse issues page
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