Improving the Variability Function in Case of a Monotonic Probability Distribution

Sans W., Zhai X., Stübner D., Sen S., Binder A. and Collani E. V.
Additional contact information
Sans W.: Institute of Applied Mathematics and Statistics, Sanderring 2, D-97070 Würzburg, Germany
Zhai X.: Institute of Applied Mathematics and Statistics, Sanderring 2, D-97070 Würzburg, Germany
Stübner D.: Institute of Applied Mathematics and Statistics, Sanderring 2, D-97070 Würzburg, Germany
Sen S.: Institute of Applied Mathematics and Statistics, Sanderring 2, D-97070 Würzburg, Germany
Binder A.: University of Applied Sciences Würzburg, Department of Computer Science, Münzstr. 9, D-97070 Würzburg, Germany
Collani E. V.: Institute of Economics, Sanderring 2, D-97070 Würzburg, Germany

Stochastics and Quality Control, 2005, vol. 20, issue 1, 121-142

Abstract: In [v. Collani, Theoretical Stochastics, Heldermann Verlag, 2004] the Bernoulli Space is introduced as fundamental model of uncertainty replacing Kolmogorov's probability space which though appropriate for defining a special branch of mathematics has hardly importance for describing real world. In [Stübner, Sans, Zhai, v. Collani, Economic Quality Control 19: 215-228, 2004] a general method for improving the variability function χ of a given Bernoulli Space is proposed. Subsequently this method has been applied to the case of uniform distributions in [Sans, Stübner, Sen, v. Collani, iapqr transactions 30: 2005]. In this paper the method is extended to cover the monotonic probability distributions.

Date: 2005
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DOI: 10.1515/EQC.2005.121

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