表紙画像

Empirical distributions of parameter estimates in binary logistic regression using bootstrap

Bootstrapping is a famous statistical tool that involves resampling procedure to select sample from a population. In this study, we applied random-x bootstrap in binary logistic regression for published data set namely Umaru Impact data. We conducted bootstrap for the coefficient by using SAS (Stati...

詳細記述

保存先:
書誌詳細
主要な著者: Fitrianto, Anwar, Ng, Mei Cing
フォーマット: 論文
言語:English
出版事項: Hikari 2014
オンライン･アクセス:http://psasir.upm.edu.my/id/eprint/37433/1/Empirical%20Distributions%20of%20Parameter%20Estimates.pdf
http://psasir.upm.edu.my/id/eprint/37433/
http://www.m-hikari.com/ijma/ijma-2014/ijma-13-16-2014/fitriantoIJMA13-16-2014-2.pdf
タグ: タグ追加
タグなし, このレコードへの初めてのタグを付けませんか!
id my.upm.eprints.37433
record_format eprints
spelling my.upm.eprints.374332015-09-15T10:10:23Z http://psasir.upm.edu.my/id/eprint/37433/ Empirical distributions of parameter estimates in binary logistic regression using bootstrap Fitrianto, Anwar Ng, Mei Cing Bootstrapping is a famous statistical tool that involves resampling procedure to select sample from a population. In this study, we applied random-x bootstrap in binary logistic regression for published data set namely Umaru Impact data. We conducted bootstrap for the coefficient by using SAS (Statistical Analysis System). We observe the distribution of the estimated coefficients with different sample sizes. After conducting B=10000 bootstrap replications, we found that the distribution of parameters estimates is nearly normal. Hikari 2014 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/37433/1/Empirical%20Distributions%20of%20Parameter%20Estimates.pdf Fitrianto, Anwar and Ng, Mei Cing (2014) Empirical distributions of parameter estimates in binary logistic regression using bootstrap. International Journal of Mathematical Analysis, 8 (15). pp. 721-726. ISSN 1312-8876; ESSN: 1314-7579 http://www.m-hikari.com/ijma/ijma-2014/ijma-13-16-2014/fitriantoIJMA13-16-2014-2.pdf 10.12988/ijma.2014.4394
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Bootstrapping is a famous statistical tool that involves resampling procedure to select sample from a population. In this study, we applied random-x bootstrap in binary logistic regression for published data set namely Umaru Impact data. We conducted bootstrap for the coefficient by using SAS (Statistical Analysis System). We observe the distribution of the estimated coefficients with different sample sizes. After conducting B=10000 bootstrap replications, we found that the distribution of parameters estimates is nearly normal.
format Article
author Fitrianto, Anwar
Ng, Mei Cing
spellingShingle Fitrianto, Anwar
Ng, Mei Cing
Empirical distributions of parameter estimates in binary logistic regression using bootstrap
author_facet Fitrianto, Anwar
Ng, Mei Cing
author_sort Fitrianto, Anwar
title Empirical distributions of parameter estimates in binary logistic regression using bootstrap
title_short Empirical distributions of parameter estimates in binary logistic regression using bootstrap
title_full Empirical distributions of parameter estimates in binary logistic regression using bootstrap
title_fullStr Empirical distributions of parameter estimates in binary logistic regression using bootstrap
title_full_unstemmed Empirical distributions of parameter estimates in binary logistic regression using bootstrap
title_sort empirical distributions of parameter estimates in binary logistic regression using bootstrap
publisher Hikari
publishDate 2014
url http://psasir.upm.edu.my/id/eprint/37433/1/Empirical%20Distributions%20of%20Parameter%20Estimates.pdf
http://psasir.upm.edu.my/id/eprint/37433/
http://www.m-hikari.com/ijma/ijma-2014/ijma-13-16-2014/fitriantoIJMA13-16-2014-2.pdf
_version_ 1643831982870757376
score 13.251813

類似資料