Confidence intervals based on resampling methods using ridge estimator in linear regression model

Confidence intervals based on resampling methods using ridge estimator in linear regression model

In multiple regression analysis, the use of ridge regression estimator over the conventional ordinary least squares estimator was suggested by Hoerl and Kennard in 1970 to beat the problem of multicollinearity that may exist among the independent variables. Keeping this in mind, in the present study...

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Bibliographic Details
Main Authors: Yogendra P Chaubey, Mansi Khurana, Shalini Chandra
Format: Article
Language:English
Published: BİSKA Bilisim Company 2018-11-01
Series:New Trends in Mathematical Sciences
Subjects:
Regression analysis
multicollinearity
confidence intervals
Jackknife technique
bootstrap technique.
Online Access:https://ntmsci.com/ajaxtool/GetArticleByPublishedArticleId?PublishedArticleId=8477
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spelling doaj-b4ee2768809d41049bcbd2c5508149dc2020-11-25T00:35:05ZengBİSKA Bilisim CompanyNew Trends in Mathematical Sciences2147-55202147-55202018-11-0164778610.20852/ntmsci.2018.3188477Confidence intervals based on resampling methods using ridge estimator in linear regression modelYogendra P Chaubey0Mansi Khurana1Shalini Chandra2Yogendra P Chaubey3Mansi Khurana4Shalini Chandra5Concordia UniversityThe NorthCap University, GurgaonBanasthali UniversityConcordia UniversityThe NorthCap University, GurgaonBanasthali UniversityIn multiple regression analysis, the use of ridge regression estimator over the conventional ordinary least squares estimator was suggested by Hoerl and Kennard in 1970 to beat the problem of multicollinearity that may exist among the independent variables. Keeping this in mind, in the present study, the authors intend to develop and compare different confidence intervals for regression coefficients based on ridge regression estimator using bootstrap and jackknife methodology. For comparison, the coverage probabilities and confidence widths are calculated through a simulation study for the data which suffers from the problem of multicollinearityhttps://ntmsci.com/ajaxtool/GetArticleByPublishedArticleId?PublishedArticleId=8477Regression analysismulticollinearityconfidence intervalsJackknife techniquebootstrap technique.
collection DOAJ
language English
format Article
sources DOAJ
author Yogendra P Chaubey
Mansi Khurana
Shalini Chandra
Yogendra P Chaubey
Mansi Khurana
Shalini Chandra
spellingShingle Yogendra P Chaubey
Mansi Khurana
Shalini Chandra
Yogendra P Chaubey
Mansi Khurana
Shalini Chandra
Confidence intervals based on resampling methods using ridge estimator in linear regression model
New Trends in Mathematical Sciences
Regression analysis
multicollinearity
confidence intervals
Jackknife technique
bootstrap technique.
author_facet Yogendra P Chaubey
Mansi Khurana
Shalini Chandra
Yogendra P Chaubey
Mansi Khurana
Shalini Chandra
author_sort Yogendra P Chaubey
title Confidence intervals based on resampling methods using ridge estimator in linear regression model
title_short Confidence intervals based on resampling methods using ridge estimator in linear regression model
title_full Confidence intervals based on resampling methods using ridge estimator in linear regression model
title_fullStr Confidence intervals based on resampling methods using ridge estimator in linear regression model
title_full_unstemmed Confidence intervals based on resampling methods using ridge estimator in linear regression model
title_sort confidence intervals based on resampling methods using ridge estimator in linear regression model
publisher BİSKA Bilisim Company
series New Trends in Mathematical Sciences
issn 2147-5520
2147-5520
publishDate 2018-11-01
description In multiple regression analysis, the use of ridge regression estimator over the conventional ordinary least squares estimator was suggested by Hoerl and Kennard in 1970 to beat the problem of multicollinearity that may exist among the independent variables. Keeping this in mind, in the present study, the authors intend to develop and compare different confidence intervals for regression coefficients based on ridge regression estimator using bootstrap and jackknife methodology. For comparison, the coverage probabilities and confidence widths are calculated through a simulation study for the data which suffers from the problem of multicollinearity
topic Regression analysis
multicollinearity
confidence intervals
Jackknife technique
bootstrap technique.
url https://ntmsci.com/ajaxtool/GetArticleByPublishedArticleId?PublishedArticleId=8477
work_keys_str_mv AT yogendrapchaubey confidenceintervalsbasedonresamplingmethodsusingridgeestimatorinlinearregressionmodel
AT mansikhurana confidenceintervalsbasedonresamplingmethodsusingridgeestimatorinlinearregressionmodel
AT shalinichandra confidenceintervalsbasedonresamplingmethodsusingridgeestimatorinlinearregressionmodel
AT yogendrapchaubey confidenceintervalsbasedonresamplingmethodsusingridgeestimatorinlinearregressionmodel
AT mansikhurana confidenceintervalsbasedonresamplingmethodsusingridgeestimatorinlinearregressionmodel
AT shalinichandra confidenceintervalsbasedonresamplingmethodsusingridgeestimatorinlinearregressionmodel
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