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A Generalization of the Variance by Using the Ordered Weighted Average

  • Conference paper
Modeling and Simulation in Engineering, Economics, and Management (MS 2013)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 145))

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Abstract

The ordered weighted average is an aggregation operator that provides a parameterized family of aggregation operators between the minimum and the maximum. This paper analyzes the use of the ordered weighted average in the variance. It presents several extensions by using a unified framework between the weighted average and the ordered weighted average. Furthermore, it also develops other generalizations with induced aggregation operators and by using quasi-arithmetic means.

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Author information

Authors and Affiliations

  1. Department of Econometrics, Riskcenter – IREA, University of Barcelona, Av. Diagonal 690, 08034, Barcelona, Spain

    José M. Merigó & Montserrat Guillén

  2. Manchester Business School, University of Manchester, Booth Street West, M15 6PB, Manchester, UK

    José M. Merigó

  3. Department of Economics, University of Cantabria, Santander, Spain

    José M. Sarabia

Authors
  1. José M. Merigó
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  2. Montserrat Guillén
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  3. José M. Sarabia
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Editor information

Editors and Affiliations

  1. Department of Finance and Accounting, University Jaume I, Castelló de la Plana, Spain

    María Ángeles Fernández-Izquierdo  & María Jesús Muñoz-Torres  & 

  2. Department of Business Administration and Marketing, University Jaume I, Castellón de la Plana, Spain

    Raúl León

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Merigó, J.M., Guillén, M., Sarabia, J.M. (2013). A Generalization of the Variance by Using the Ordered Weighted Average. In: Fernández-Izquierdo, M.Á., Muñoz-Torres, M.J., León, R. (eds) Modeling and Simulation in Engineering, Economics, and Management. MS 2013. Lecture Notes in Business Information Processing, vol 145. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38279-6_24

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  • DOI: https://doi.org/10.1007/978-3-642-38279-6_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38278-9

  • Online ISBN: 978-3-642-38279-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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