Grid-based histogram arithmetic for the probabilistic analysis of functions

Carreras Vaquer, Carlos and Hermenegildo, Manuel V. (2000). Grid-based histogram arithmetic for the probabilistic analysis of functions. In: "4th International Symposium, SARA 2000", July 26-29, 2000, Horseshoe Bay, USA. ISBN 9783540678397.

Description

Title: Grid-based histogram arithmetic for the probabilistic analysis of functions
Author/s:
  • Carreras Vaquer, Carlos
  • Hermenegildo, Manuel V.
Item Type: Presentation at Congress or Conference (Article)
Event Title: 4th International Symposium, SARA 2000
Event Dates: July 26-29, 2000
Event Location: Horseshoe Bay, USA
Title of Book: Abstraction, Reformulation, and Approximation
Date: 2000
ISBN: 9783540678397
Volume: 1864
Subjects:
Freetext Keywords: Interval computations, probabilistic analysis, estimation, approximate arithmetic, abstract interpretation, cálculo de intervalos, análisis probabilístico, estimación, aproximación aritmética, interpretación de resúmenes.
Faculty: Facultad de Informática (UPM)
Department: Inteligencia Artificial
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

The selection of predefined analytic grids (partitions of the numeric ranges) to represent input and output functions as histograms has been proposed as a mechanism of approximation in order to control the tradeoff between accuracy and computation times in several áreas ranging from simulation to constraint solving. In particular, the application of interval methods for probabilistic function characterization has been shown to have advantages over other methods based on the simulation of random samples. However, standard interval arithmetic has always been used for the computation steps. In this paper, we introduce an alternative approximate arithmetic aimed at controlling the cost of the interval operations. Its distinctive feature is that grids are taken into account by the operators. We apply the technique in the context of probability density functions in order to improve the accuracy of the probability estimates. Results show that this approach has advantages over existing approaches in some particular situations, although computation times tend to increase significantly when analyzing large functions.

More information

Item ID: 14379
DC Identifier: https://oa.upm.es/14379/
OAI Identifier: oai:oa.upm.es:14379
Official URL: http://link.springer.com/chapter/10.1007%2F3-540-4...
Deposited by: Biblioteca Facultad de Informatica
Deposited on: 01 Feb 2013 08:11
Last Modified: 27 Feb 2023 12:31
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