Interval estimation for a binomial proportion: a bootstrap approach
| dc.contributor.author | Mantalos, P. | en |
| dc.contributor.author | Zografos, K. | en |
| dc.date.accessioned | 2015-11-24T17:24:53Z | |
| dc.date.available | 2015-11-24T17:24:53Z | |
| dc.identifier.issn | 0094-9655 | - |
| dc.identifier.uri | https://olympias.lib.uoi.gr/jspui/handle/123456789/12969 | |
| dc.rights | Default Licence | - |
| dc.subject | agresti and coull confidence interval | en |
| dc.subject | binomial distribution | en |
| dc.subject | bootstrap | en |
| dc.subject | confidence intervals | en |
| dc.subject | coverage probability | en |
| dc.subject | confidence-intervals | en |
| dc.title | Interval estimation for a binomial proportion: a bootstrap approach | en |
| heal.abstract | This paper discusses the classic but still current problem of interval estimation of a binomial proportion. Bootstrap methods are presented for constructing such confidence intervals in a routine, automatic way. Three confidence intervals for a binomial proportion are compared and studied by means of a simulation study, namely: the Wald confidence interval, the Agresti-Coull interval and the bootstrap-t interval. A new confidence interval, the Agresti-Coull interval with bootstrap critical values, is also introduced and its good behaviour related to the average coverage probability is established by means of simulations. | en |
| heal.access | campus | - |
| heal.fullTextAvailability | TRUE | - |
| heal.identifier.primary | Doi 10.1080/00949650701749356 | - |
| heal.identifier.secondary | <Go to ISI>://000260497300010 | - |
| heal.journalName | Journal of Statistical Computation and Simulation | en |
| heal.journalType | peer reviewed | - |
| heal.language | en | - |
| heal.publicationDate | 2008 | - |
| heal.publisher | Taylor & Francis | en |
| heal.recordProvider | Πανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μαθηματικών | el |
| heal.type | journalArticle | - |
| heal.type.el | Άρθρο Περιοδικού | el |
| heal.type.en | Journal article | en |
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