Subtitle:

Raport Badawczy = Research Report ; RB/6/2005

Publisher:

Instytut Badań Systemowych. Polska Akademia Nauk ; Systems Research Institute. Polish Academy of Sciences

Place of publishing:

Warszawa

Description:

19, [1] pages ; 21 cm ; Bibliography p. 18-19

Type of object:

Book/Chapter

Abstract:

The paper deals with the estimation problem of model parameter values, in tasks where overestimation implies results other than underestimation, and where losses arising from this can be described by a quadratic function with different coefficients characterizing positive and negative errors. In the approach presented, the Bayes decision rule was used, allowing to minimize potential losses. Calculation algorithms were based on the theory of statistical kernel estimators, which frees the method from distribution type. The result constitutes a complete numerical procedure enabling to effectively calculate the value of an identified parameter or - in the multidimensional case - the vector of parameters. The method is aimed at both contemporary approaches to uncertainty modeling: probabilistic and fuzzy logic. It is universal in nature and can be applied in a wide range of tasks of engineering, economy, sociology, biomedicine and other related fields.

Relation:

Raport Badawczy = Research Report

Detailed Resource Type:

Report

Resource Identifier:

oai:rcin.org.pl:139672

Source:

RB-2005-06

Language:

eng

Language of abstract:

eng

Rights:

Creative Commons Attribution BY 4.0 license

Terms of use:

Copyright-protected material. [CC BY 4.0] May be used within the scope specified in Creative Commons Attribution BY 4.0 license, full text available at: ; -

Digitizing institution:

Systems Research Institute of the Polish Academy of Sciences

Original in:

Library of Systems Research Institute PAS

Projects co-financed by:

Operational Program Digital Poland, 2014-2020, Measure 2.3: Digital accessibility and usefulness of public sector information; funds from the European Regional Development Fund and national co-financing from the state budget.

Access:

Open