JMASM39: Algorithm for combining robust and bootstrap in multiple linear model regression

JMASM39: Algorithm for combining robust and bootstrap in multiple linear model regression

The aim of bootstrapping is to approximate the sampling distribution of some estimator.An algorithm for combining method is given in SAS, along with applications and visualizations.

Bibliographic Details
Main Authors: Wan Ahmad, Wan Muhamad Amir, Ghazali, Puspa Liza, Mohd Ibrahim, Mohamad Shafiq, Aleng, Azlida, A. Rahim, Hanafi, Abdullah, Zailani
Format: Article
Language:English
Published: Journal of Modern Applied Statistical Methods Inc 2016
Subjects:
QA276 Mathematical Statistics
Online Access:http://irep.iium.edu.my/72171/
http://irep.iium.edu.my/72171/
http://irep.iium.edu.my/72171/
http://irep.iium.edu.my/72171/1/Algorithm%20for%20Combining%20In%20Multiple%20Linear%20Model%20Regression.pdf
id iium-72171
recordtype eprints
spelling iium-721712019-05-16T06:26:39Z http://irep.iium.edu.my/72171/ JMASM39: Algorithm for combining robust and bootstrap in multiple linear model regression Wan Ahmad, Wan Muhamad Amir Ghazali, Puspa Liza Mohd Ibrahim, Mohamad Shafiq Aleng, Azlida A. Rahim, Hanafi Abdullah, Zailani QA276 Mathematical Statistics The aim of bootstrapping is to approximate the sampling distribution of some estimator.An algorithm for combining method is given in SAS, along with applications and visualizations. Journal of Modern Applied Statistical Methods Inc 2016-05 Article PeerReviewed application/pdf en http://irep.iium.edu.my/72171/1/Algorithm%20for%20Combining%20In%20Multiple%20Linear%20Model%20Regression.pdf Wan Ahmad, Wan Muhamad Amir and Ghazali, Puspa Liza and Mohd Ibrahim, Mohamad Shafiq and Aleng, Azlida and A. Rahim, Hanafi and Abdullah, Zailani (2016) JMASM39: Algorithm for combining robust and bootstrap in multiple linear model regression. Journal of Modern Applied Statistical Methods, 15 (1). pp. 884-892. ISSN 1538 − 9472 https://digitalcommons.wayne.edu/cgi/viewcontent.cgi?article=1912&context=jmasm 10.22237/jmasm/1462077900
repository_type Digital Repository
institution_category Local University
institution International Islamic University Malaysia
building IIUM Repository
collection Online Access
language English
topic QA276 Mathematical Statistics
spellingShingle QA276 Mathematical Statistics
Wan Ahmad, Wan Muhamad Amir
Ghazali, Puspa Liza
Mohd Ibrahim, Mohamad Shafiq
Aleng, Azlida
A. Rahim, Hanafi
Abdullah, Zailani
JMASM39: Algorithm for combining robust and bootstrap in multiple linear model regression
description The aim of bootstrapping is to approximate the sampling distribution of some estimator.An algorithm for combining method is given in SAS, along with applications and visualizations.
format Article
author Wan Ahmad, Wan Muhamad Amir
Ghazali, Puspa Liza
Mohd Ibrahim, Mohamad Shafiq
Aleng, Azlida
A. Rahim, Hanafi
Abdullah, Zailani
author_facet Wan Ahmad, Wan Muhamad Amir
Ghazali, Puspa Liza
Mohd Ibrahim, Mohamad Shafiq
Aleng, Azlida
A. Rahim, Hanafi
Abdullah, Zailani
author_sort Wan Ahmad, Wan Muhamad Amir
title JMASM39: Algorithm for combining robust and bootstrap in multiple linear model regression
title_short JMASM39: Algorithm for combining robust and bootstrap in multiple linear model regression
title_full JMASM39: Algorithm for combining robust and bootstrap in multiple linear model regression
title_fullStr JMASM39: Algorithm for combining robust and bootstrap in multiple linear model regression
title_full_unstemmed JMASM39: Algorithm for combining robust and bootstrap in multiple linear model regression
title_sort jmasm39: algorithm for combining robust and bootstrap in multiple linear model regression
publisher Journal of Modern Applied Statistical Methods Inc
publishDate 2016
url http://irep.iium.edu.my/72171/
http://irep.iium.edu.my/72171/
http://irep.iium.edu.my/72171/
http://irep.iium.edu.my/72171/1/Algorithm%20for%20Combining%20In%20Multiple%20Linear%20Model%20Regression.pdf
first_indexed 2023-09-18T21:42:18Z
last_indexed 2023-09-18T21:42:18Z
_version_ 1777413221155602432

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