Induced owa operators in linear regression

Statistical linear regression (LR) is a tool used in developing mathematical models for applications in business (Maturo & Hoskova- mayerova, 2017), economics forecasting (Chudik, Kapetanios, & Hashem, 2018), natural sciences (Kilmer & Rodriguez, 2016), engineering (Braun, Altan, & B...

詳細記述

書誌詳細
主要な著者: Avilés Ochoa, Ezequiel, Flores Sosa, Martha, Merigó, José M
フォーマット: Documento de Conferencia
言語:spa
出版事項: 2021
オンライン・アクセス:http://repositorio.uptc.edu.co/handle/001/5605
その他の書誌記述
要約:Statistical linear regression (LR) is a tool used in developing mathematical models for applications in business (Maturo & Hoskova- mayerova, 2017), economics forecasting (Chudik, Kapetanios, & Hashem, 2018), natural sciences (Kilmer & Rodriguez, 2016), engineering (Braun, Altan, & Beck, 2014), and so on. The most common statistical method used to estimate the parameters is the least-squares regression, which works by finding the “best curve” through the data that minimizes the residual sum of squares. It has some advantages, among them, simplicity and ease of use (Raposo, 2016; Bettis & Fairlie, 2001), however atypical data and the relationship of the variables with others of them can be very problematic in regression analysis.