Sufficient jackknife-after-bootstrap method for detection of influential observations in linear regression models

被引：13

作者：

Beyaztas, Ufuk ^{[1
]}

Alin, Aylin ^{[1
]}

机构：

[1] Dokuz Eylul Univ, Dept Stat, Izmir, Turkey

来源：

STATISTICAL PAPERS | 2014年 / 55卷 / 04期

关键词：

Sufficient bootstrap; Jacknife; Bootstrap; Influential observation; Regression diagnostics;

D O I：

10.1007/s00362-013-0548-4

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In this study, we adapt sufficient bootstrap into the jackknife-after-bootstrap (JaB) algorithm. The performances of the sufficient and conventional JaB methods have been compared for detecting influential observations in linear regression. Comparison is based on two real-world examples and an extensive designed simulation study. Design includes different sample sizes and various modeling scenarios. The results reveal that proposed method is a good competitor for conventional JaB method with less standard error and amount of computation.

引用

页码：1001 / 1018

页数：18

共 50 条

[41] Bayesian jackknife empirical likelihood for the error variance in linear regression models
Jiang, Hongyan
Zhao, Yichuan
[J]. JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 2022, 92 (16) : 3400 - 3413
[42] An Efficient Method of Identification of Influential Observations in Multiple Linear Regression and Its Application to Real Data
Midi, Habshah
Hendi, Hasan Talib
Uraibi, Hassan
Arasan, Jayanthi
Ismaeel, Shelan Saied
[J]. SAINS MALAYSIANA, 2023, 52 (12): : 3589 - 3602
[43] Diagnostics of multiple group influential observations for logistic regression models
Coskun, Burcin
Alpu, O.
[J]. JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 2019, 89 (16) : 3118 - 3136
[44] DETECTION OF INFLUENTIAL OBSERVATIONS IN REGRESSION-MODEL WITH AUTOCORRELATED ERRORS
HOSSAIN, A
[J]. COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 1990, 19 (03) : 1047 - 1060
[45] Jackknife estimation for smooth functions of the parametric component in partially linear regression models
You, JH
Chen, GM
[J]. COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2003, 32 (09) : 1817 - 1833
[46] Delete-group Jackknife Estimate in Partially Linear Regression Models with Heteroscedasticity
Jin-hong You
Gemai Chen
[J]. Acta Mathematicae Applicatae Sinica, 2003, 19 (4) : 599 - 610
[47] Delete-group Jackknife Estimate in Partially Linear Regression Models with Heteroscedasticity
Jin-hong You
Gemai Chen
[J]. Acta Mathematicae Applicatae Sinica, 2003, (04) : 599 - 610
[48] Bootstrap tests for the error distribution in linear and nonparametric regression models
Neumeyer, Natalie
Dette, Holger
Nagel, Eva-Renate
[J]. AUSTRALIAN & NEW ZEALAND JOURNAL OF STATISTICS, 2006, 48 (02) : 129 - 156
[49] BARTLETT CORRECTION AND THE BOOTSTRAP IN NORMAL LINEAR-REGRESSION MODELS
RAYNER, RK
[J]. ECONOMICS LETTERS, 1990, 33 (03) : 255 - 258
[50] Bootstrap inference in functional linear regression models with scalar response
Yeon, Hyemin
Dai, Xiongtao
Nordman, Daniel J.
[J]. BERNOULLI, 2023, 29 (04) : 2599 - 2626

← 1 2 3 4 5 →