Dual models for possibilistic regression analysis

DOI10.1016/j.csda.2006.04.005zbMath1157.62469OpenAlexW1993791320WikidataQ57597826 ScholiaQ57597826MaRDI QIDQ1010360

Hideo Tanaka, Peijun Guo

Publication date: 6 April 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2006.04.005

zbMATH Keywords

linear programmingquadratic programmingrough setspossibilistic regression analysis

Mathematics Subject Classification ID

Linear inference, regression (62J99) Applications of mathematical programming (90C90)

Related Items (18)

The normalized interval regression model with outlier detection and its real-world application to house pricing problems ⋮ A multiple linear regression model for imprecise information ⋮ Least-squares approach to regression modeling in full interval-valued fuzzy environment ⋮ From fuzzy regression to gradual regression: interval-based analysis and extensions ⋮ Prediction Model with Interval Data -Toward Practical Applications- ⋮ Conservative and aggressive rough SVR modeling ⋮ Eliciting dual interval probabilities from interval comparison matrices ⋮ Dual possibilistic regression analysis using support vector networks ⋮ A set arithmetic-based linear regression model for modelling interval-valued responses through real-valued variables ⋮ On the possibilistic approach to linear regression models involving uncertain, indeterminate or interval data ⋮ Formulation of A Sale Price Prediction Model Based on Fuzzy Regression Analysis ⋮ Rough support vector regression ⋮ Management of uncertainty in statistical reasoning: the case of regression analysis ⋮ A revisited approach to linear fuzzy regression using trapezoidal fuzzy intervals ⋮ Modeling customer satisfaction with new product design using a flexible fuzzy regression-data envelopment analysis algorithm ⋮ The fuzzy approach to statistical analysis ⋮ A WEIGHTED LINEAR REGRESSION MODEL FOR IMPERCISE RESPONSE ⋮ Least Squares Method for L-R Fuzzy Variables

Cites Work

• Fuzzy least squares
• Possibilistic linear regression analysis for fuzzy data
• Interval priorities in AHP by interval regression analysis
• Identification of possibilistic linear systems by quadratic membership functions of fuzzy parameters
• Linear regression analysis for fuzzy/crisp input and fuzzy/crisp output data
• Fuzzy estimates of regression parameters in linear regression models for imprecise input and output data
• Fuzzy data analysis by possibilistic linear models
• Possibilistic linear systems and their application to the linear regression model
• Possibilistic data analysis for operations research
• Insight of a fuzzy regression model
• Fuzzy regression by fuzzy number neural networks
• Upper and lower approximation models in interval regression using regression quantile techniques
• A possibilistic approach to latent component analysis for symmetric fuzzy data
• Least-squares estimates in fuzzy regression analysis.
• Decision analysis based on fused double exponential possibility distributions.
• Multiobjective fuzzy regression with central tendency and possibilistic properties
• Exponential possibility regression analysis
• Upper and lower possibility distributions of fuzzy decision variables in upper level decision problems
• Rough classification
• Linear Regression Analysis with Fuzzy Model
• Outliers detection and confidence interval modification in fuzzy regression.
• Fuzzy regression using asymmetric fuzzy coefficients and fuzzified neural networks
• Unnamed Item
• Unnamed Item

This page was built for publication: Dual models for possibilistic regression analysis