Force implication: a new approach to human reasoning
Fuzzy Sets and Systems
The nature of statistical learning theory
The nature of statistical learning theory
Machine Learning
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy sets in decision analysis, operations research and statistics
Fuzzy regression methods—a comparative assessment
Fuzzy Sets and Systems
A theoretical framework for data mining: the "informational paradigm"
Computational Statistics & Data Analysis - Nonlinear methods and data mining
Least-squares fuzzy regression with fuzzy random variables
Fuzzy Sets and Systems
Uncertainty and Information: Foundations of Generalized Information Theory
Uncertainty and Information: Foundations of Generalized Information Theory
Mathematics of Uncertainty: Ideas, Methods, Application Problems (Studies in Fuzziness and Soft Computing)
A weighted fuzzy c-means clustering model for fuzzy data
Computational Statistics & Data Analysis
Random and fuzzy sets in coarse data analysis
Computational Statistics & Data Analysis
Regression with fuzzy random data
Computational Statistics & Data Analysis
Dual models for possibilistic regression analysis
Computational Statistics & Data Analysis
Least squares estimation of a linear regression model with LR fuzzy response
Computational Statistics & Data Analysis
The fuzzy approach to statistical analysis
Computational Statistics & Data Analysis
Generalized theory of uncertainty (GTU)-principal concepts and ideas
Computational Statistics & Data Analysis
Tools for fuzzy random variables: Embeddings and measurabilities
Computational Statistics & Data Analysis
Bootstrap approach to the multi-sample test of means with imprecise data
Computational Statistics & Data Analysis
Multi-sample test-based clustering for fuzzy random variables
International Journal of Approximate Reasoning
An enhanced fuzzy linear regression model with more flexible spreads
Fuzzy Sets and Systems
A linear regression model for imprecise response
International Journal of Approximate Reasoning
Fuzzy clustering of time series in the frequency domain
Information Sciences: an International Journal
Maximum likelihood estimation from fuzzy data using the EM algorithm
Fuzzy Sets and Systems
A Midpoint--Radius approach to regression with interval data
International Journal of Approximate Reasoning
Information Sciences: an International Journal
Self-Organizing Maps for imprecise data
Fuzzy Sets and Systems
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Statistical Reasoning is affected by various sources of Uncertainty: randomness, imprecision, vagueness, partial ignorance, etc. Traditional statistical paradigms (such as Statistical Inference, Exploratory Data Analysis, Statistical Learning) are not capable to account for the complex action of Uncertainty in real life applications of Statistical Reasoning. A conceptual framework, called ''Informational Paradigm'', is introduced in order to analyze the role of Information and Uncertainty in these complex contexts. Regression Analysis is taken as the reference problem for developing the discussion. Three basic sources of Uncertainty are considered in this respect: (1) uncertainty about the relationship between response and explanatory variables; (2) uncertainty about the relationship between the observed data and the ''universe'' of possible data; (3) uncertainty about the observed values of the variables (imprecision, vagueness). Some of the available methods for coping with these different types of Uncertainty are discussed in an orderly way, from the simpler cases where only one source at a time is dealt with, to the more complex ones where all sources act together. Probabilistic and Fuzzy-Possibilistic tools are exploited, in this connection. In spite of the recent relevant contributions in this domain, the weaknesses and deficiencies of the current procedures for managing Uncertainty in Regression Analysis, as well as in other areas of Statistics, are emphasized. The elements of a generalized system of Statistical Reasoning, capable to deal with the various sources of Uncertainty, are finally introduced and the lines for future investigation in this perspective are indicated.