The smoothed bootstrap fine-tuning
Authors:
- Renata Dwornicka,
- Andrii Goroshko,
- Jacek Pietraszek
Abstract
The bootstrap method is a well-known method to gather a full probability distribution from the dataset of a small sample. The simple bootstrap i.e. resampling from the raw dataset often leads to a significant irregularities in a shape of resulting empirical distribution due to the discontinuity of a support. The remedy for these irregularities is the smoothed bootstrap: a small random shift of source points before each resampling. This shift is controlled by specifically selected distributions. The key issue is such parameter settings of these distributions to achieve the desired characteristics of the empirical distribution. This paper describes an example of this procedure.
- Record ID
- CUT4c3dff6fe2854218aa730935522ebaab
- Publication categories
- ; ;
- Author
- Journal series
- System Safety: Human - Technical Facility - Environment, ISSN 2657-5450
- Issue year
- 2019
- Vol
- 1
- No
- 1
- Pages
- 716-723
- Other elements of collation
- rys.; tab.; Bibliografia (na s.) - 722-723; Oznaczenie streszczenia - Abstr.; Numeracja w czasopiśmie - Vol. 1, Iss. 1
- Conference
- 7th International Conference System Safety: Human - Technical Facility - Environment (CzOTO 2018), 2018, 12-12-2018 - 14-12-2018, Zakopane, Polska
- Keywords in English
- smoothed bootstrap, statistics, design of experiments, numerical simulation
- DOI
- DOI:10.2478/czoto-2019-0091 Opening in a new tab
- URL
- https://content.sciendo.com/view/journals/czoto/1/1/article-p716.xml Opening in a new tab
- Language
- eng (en) English
- License
- Score (nominal)
- 5
- Uniform Resource Identifier
- https://cris.pk.edu.pl/info/article/CUT4c3dff6fe2854218aa730935522ebaab/
- URN
urn:pkr-prod:CUT4c3dff6fe2854218aa730935522ebaab
* presented citation count is obtained through Internet information analysis, and it is close to the number calculated by the Publish or PerishOpening in a new tab system.