@inproceedings{b045e31e3edc4416917f8204d932dc57,

title = "Risk analysis with reference class forecasting adopting tolerance regions",

abstract = "The target of this paper is to demonstrate the benefits of using tolerance regions statistics in risk analysis. In particular, adopting the expected beta content tolerance regions as an alternative approach for choosing the optimal order of a response polynomial it is possible to improve results in reference class forecasting methodology. Reference class forecasting tries to predict the result of a planned action based on actual outcomes in a reference class of similar actions to that being forecast. Scientists/analysts do not usually work with a best fitting polynomial according to a prediction criterion. The present paper proposes an algorithm, which selects the best response polynomial, as far as a future prediction is concerned for reference class forecasting. The computational approach adopted is discussed with the help of an example of a relevant application.",

keywords = "General linear regression, Predictive models, Reference class forecasting, Risk analysis, Tolerance regions",

author = "Vasilios Zarikas and Kitsos, {Christos P.}",

year = "2015",

month = jan,

day = "1",

doi = "10.1007/978-3-319-18029-8_18",

language = "English",

isbn = "9783319180281",

series = "Springer Proceedings in Mathematics and Statistics",

publisher = "Springer New York",

pages = "235--247",

editor = "Alexandros Rigas and Kitsos, {Christos P.} and Sneh Gulati and Oliveira, {Teresa A.}",

booktitle = "Theory and Practice of Risk Assessment - ICRA5 2013",

address = "United States",

note = "5th International Conference on Risk Analysis, ICRA5 2013 ; Conference date: 30-05-2013 Through 01-06-2013",

}