Professor Frank Coolen frank.coolen@durham.ac.uk
Professor
Nonparametric predictive comparison of proportions
Coolen, F.P.A.; Coolen-Schrijner, P.
Authors
P. Coolen-Schrijner
Abstract
We use the lower and upper predictive probabilities from Coolen [1998. Low structure imprecise predictive inference for Bayes’ problem. Statist. Probab. Lett. 36, 349–357] to compare future numbers of successes in Bernoulli trials for different groups. We consider both pairwise and multiple comparisons. These inferences are in terms of lower and upper probabilities that the number of successes in m future trials from one group exceeds the number of successes in m future trials from another group, or such numbers from all other groups. We analyse these lower and upper probabilities via application to two data sets from the literature, and discuss the imprecision in relation to m.
Citation
Coolen, F., & Coolen-Schrijner, P. (2007). Nonparametric predictive comparison of proportions. Journal of Statistical Planning and Inference, 137(1), 23-33. https://doi.org/10.1016/j.jspi.2005.11.008
Journal Article Type | Article |
---|---|
Publication Date | 2007-01 |
Deposit Date | Apr 26, 2007 |
Journal | Journal of Statistical Planning and Inference |
Print ISSN | 0378-3758 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 137 |
Issue | 1 |
Pages | 23-33 |
DOI | https://doi.org/10.1016/j.jspi.2005.11.008 |
Keywords | Bernoulli trials, Lower and upper probabilities, Multiple comparisons, Nonparametric predictive inference, Pairwise comparisons. |
You might also like
Logic Differential Calculus for Reliability Analysis Based on Survival Signature
(2022)
Journal Article
A Cost-Sensitive Imprecise Credal Decision Tree based on Nonparametric Predictive Inference
(2022)
Journal Article
Pricing exotic options in the incomplete market: an imprecise probability method
(2022)
Journal Article
Counterfactual explanation of machine learning survival models
(2021)
Journal Article
Statistical reproducibility for pairwise t-tests in pharmaceutical research
(2021)
Journal Article
Downloadable Citations
About Durham Research Online (DRO)
Administrator e-mail: dro.admin@durham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search