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Improving the Variability Function in Case of a Monotonic Probability Distribution
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W. Sans
Veröffentlicht/Copyright:
15. März 2010
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.
Published Online: 2010-03-15
Published in Print: 2005-April
© Heldermann Verlag
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Artikel in diesem Heft
- Statistical Performance of Control Charts
- A Note on Optimum Chain Sampling (ChSP-1)
- A Modified Quantile Estimator Using Extreme-Value Theory with Applications
- Stochastics in the Manufacture and Operation of Fuel Assemblies for Nuclear Power Plants
- Improving the Maintenance System of Tippers A Case Study
- Two Examples of a Successful Multivariate Quantitative Analysis in Industry
- Robustness of Group Runs Control Chart to Non-normality
- Run and Frequency Quotas Under Markovian Fashion and their Application in Risk Analysis
- Reliability For A Bivariate Gamma Distribution
- Improving the Variability Function in Case of a Monotonic Probability Distribution
- A Bivariate Weibull Regression Model
