Constructing a Knowledge Economy Composite Indicator with Imprecise Data

Constructing imprecise probability distributions

In this current paper the following problems are addressed: (1) extending the knowledge of a partially known probability distribution function to any point of a continuous sample space, (2) constructing an imprecise probability distribution based on the knowledge of a set of credible or confidence intervals, and (3) computing the lower and upper expected values of a random continuous variable. ...

On constructing a composite indicator with multiplicative aggregation and the avoidance of zero weights in DEA

Recently there has been interest in combining the use of multiplicative aggregation together with data envelopment analysis (DEA). For example Blancas et al (2013), Cook and Zhu (2013), Giambona and Vassallo (2013); the first two of these are JORS papers. The purpose of this note is to highlight differences in the way multiplicative DEA is being applied and to draw attention to the fact that a ...

Imprecise Data and Knowledge Based OLAP

In this paper we present our approach for extending the OLAP model to include treatment of value uncertainty as part of a multidimensional model inhabited by flexible data and non-rigid hierarchical structures of organisation. A new multidimensional-cubic model named as the IF-Cube is introduced which is able to operate over data with imprecision either in the facts or in the dimensional hierar...

Non convex technologies and economic efficiency measure with imprecise data

Statistics with Imprecise Data

Article Outline Glossary I. Definition of the Subject and Its Importance II. Introduction III. Mathematical modeling of imprecise data IV. Fuzzy random variables V. Statistical analysis of random fuzzy perceptions VI.1 Fuzzy estimators and fuzzy confidence intervals VI.2 Fuzzy statistical tests VII. Statistical analysis of random fuzzy variables VIII. Future directions Bibliography Glossary Fuz...