@misc{Kulczycki_Piotr._Autor_An_2005,
 author={Kulczycki, Piotr. Autor and Mazgaj, Aleksander. Autor},
 copyright={Creative Commons Attribution BY 4.0 license},
 address={Warszawa},
 journal={Raport Badawczy = Research Report},
 howpublished={online},
 year={2005},
 publisher={Instytut Badań Systemowych. Polska Akademia Nauk},
 publisher={Systems Research Institute. Polish Academy of Sciences},
 language={eng},
 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.},
 type={Text},
 title={An algorithm for Bayes parameter identification with quadratic nonsymmetrical loss function},
 keywords={Bayesian methods, Decision support, Bayesowska reguła decyzyjna, Statistical kernel estimators},
}