Title
Representing uncertainty by possibility distributions encoding confidence bands, tolerance and prediction intervals
Abstract
For a given sample set, there are already different methods for building possibility distributions encoding the family of probability distributions that may have generated the sample set. Almost all the existing methods are based on parametric and distribution free confidence bands. In this work, we introduce some new possibility distributions which encode different kinds of uncertainties not treated before. Our possibility distributions encode statistical tolerance and prediction intervals (regions). We also propose a possibility distribution encoding the confidence band of the normal distribution which improves the existing one for all sample sizes. In this work we keep the idea of building possibility distributions based on intervals which are among the smallest intervals for small sample sizes. We also discuss the properties of the mentioned possibility distributions.
Year
DOI
Venue
2012
10.1007/978-3-642-33362-0_18
SUM
Keywords
Field
DocType
sample size,prediction interval,confidence band,normal distribution,distribution free confidence band,different kind,small sample size,representing uncertainty,sample set,probability distribution,new possibility distribution,possibility distribution,tolerance interval,confidence region
Confidence region,Statistical parameter,Stability (probability),Confidence distribution,Inverse distribution,Robust confidence intervals,CDF-based nonparametric confidence interval,Confidence and prediction bands,Statistics,Mathematics
Conference
Citations 
PageRank 
References 
2
0.38
6
Authors
3
Name
Order
Citations
PageRank
Mohammad Ghasemi Hamed1283.29
Mathieu Serrurier226726.94
Nicolas Durand320.38