An Application of Mindsadbesd Regression
Journal Title: Journal of Applied Quantitative Methods - Year 2006, Vol 1, Issue 2
Abstract
In this work, an application of the modified minsadbed (minimizing sum of absolute differences between deviations) approach for a fuzzy environment is given. This type of regression was used for a statistical model with two real parameters and experimental observations which implies real numbers (see Arthanary and Dodge2). We develop minsadbed to minsadbesd (minimizing sum of absolute differences between squared deviations) which is more suitable for our model on vague sets. The models on fuzzy sets are described by Ming, Friedman and Kandel3; these authors estimate the parameters pre-eminently using least squares. We make an attempt for another method, as in the following writing.
Authors and Affiliations
Ciprian POPESCU, Sudradjat SUPIAN
Keywords
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