• Publications
  • Influence
Least squares estimation of a linear regression model with LR fuzzy response
TLDR
A general linear regression model for studying the dependence of a LR fuzzy response variable on a set of crisp explanatory variables, along with a suitable iterative least squares estimation procedure, is introduced. Expand
  • 131
  • 4
  • PDF
A linear regression model for imprecise response
TLDR
A linear regression model with imprecise response and p real explanatory variables is analyzed. Expand
  • 75
  • 4
  • PDF
The fuzzy approach to statistical analysis
TLDR
For the last decades, research studies have been developed in which a coalition of Fuzzy Sets Theory and Statistics has been established with different purposes. Expand
  • 118
  • 3
  • PDF
Fuzzy and possibilistic clustering for fuzzy data
TLDR
The Fuzzy k-Means clustering model (FkM) is a powerful tool for classifying objects into a set of k homogeneous clusters by means of the membership degrees of an object in a cluster. Expand
  • 61
  • 2
A Fuzzy Clustering Model for Multivariate Spatial Time Series
TLDR
Clustering of multivariate spatial-time series should consider: 1) the spatial nature of the objects to be clustered; 2) the characteristics of the feature space; 3) the uncertainty associated to the assignment of a spatial unit to a given cluster on the basis of the above complex features. Expand
  • 59
  • 2
Management of uncertainty in Statistical Reasoning: The case of Regression Analysis
  • R. Coppi
  • Computer Science
  • Int. J. Approx. Reason.
  • 1 March 2008
TLDR
Statistical Reasoning is affected by various sources of Uncertainty: randomness, imprecision, vagueness, partial ignorance, etc. Expand
  • 44
  • 2
Analysis of Three-Way Data Matrices Based on Pairwise Relation Measures
The basic types of 3-way data matrices are described. The special case of one or more sets of qualitative characters observed on one or more groups of individuals is then examined. SeveralExpand
  • 13
  • 2
A theoretical framework for data mining: the informational paradigm
  • R. Coppi
  • Computer Science
  • 28 February 2002
TLDR
Data Mining (DM) is examined in a statistical perspective, as a methodological area where the objective is to extract useful information from very large databases. Expand
  • 34
  • 2
Component Models for Fuzzy Data
The fuzzy perspective in statistical analysis is first illustrated with reference to the “Informational Paradigm–allowing us to deal with different types of uncertainties related to the variousExpand
  • 49
  • 1
Multiway Data Analysis
Mathematical Aspects of Multiway Data Arrays. (Contributors: R. Coppi, F. Critchley J.B. Kruskal A. Franc J.B. Denis, T. Dhorne G. D'Aubigny, E. Polit J.M.F. ten Berge B. Leclerc). Relationships andExpand
  • 260
...
1
2
3
4
5
...