Interval that covers estimate of variance being calculated from interval data

Asymptotic algorithm for computing the sample variance of interval data

The problem of the sample variance computation for epistemic inter-val-valued data is, in general, NP-hard. Therefore, known efficient algorithms for computing variance require strong restrictions on admissible intervals like the no-subset property or heavy limitations on the number of possible intersections between intervals. A new asymptotic algorithm for computing the upper bound of the samp...

Bootstrap estimate of the variance and confidence interval of kappa.

A Bootstrap Interval Robust Data Envelopment Analysis for Estimate Efficiency and Ranking Hospitals

Data envelopment analysis (DEA) is one of non-parametric methods for evaluating efficiency of each unit. Limited resources in healthcare economy is the main reason in measuring efficiency of hospitals. In this study, a bootstrap interval data envelopment analysis (BIRDEA) is proposed for measuring the efficiency of hospitals affiliated with the Hamedan University of Medical Sciences. The propos...

EFFICIENCY MEASUREMENT OF NDEA WITH INTERVAL DATA

Data envelopment analysis (DEA) is a non-parametric technique for evaluation of relative efficiency of decision making units described by multiple inputs and outputs. It is based on solving linear programming problems. Since 1978 when basic DEA model was introduced many its modifications were formulated. Among them are two or multi-stage models with serial or parallel structure often called net...

The Maximal Variance of Fuzzy Interval

There is a well-known interpretation of fuzzy interval in the framework of the theory of imprecise probabilities [1, 2]. To get this, we associate with any fuzzy interval a possibility or necessity measure, and then consider that values of the pointed measures give us lower or upper assessments of probabilities. This interpretation was discussed in detail in [3], and there it is proposed to use...