2018
DOI: 10.1002/cem.3054
|View full text |Cite
|
Sign up to set email alerts
|

Developing a ridge estimator for the gamma regression model

Abstract: The ridge regression model has been consistently demonstrated to be an attractive shrinkage method to reduce the effects of multicollinearity. The gamma regression model is a very popular model in the application when the response variable is positively skewed. However, it is known that multicollinearity negatively affects the variance of maximum likelihood estimator of the gamma regression coefficients. To address this problem, a gamma ridge regression model has been proposed. In this study, a new estimator i… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4
1

Citation Types

0
23
0

Year Published

2020
2020
2022
2022

Publication Types

Select...
7

Relationship

1
6

Authors

Journals

citations
Cited by 46 publications
(23 citation statements)
references
References 27 publications
0
23
0
Order By: Relevance
“…The chemical dataset adopted in this study was employed in the study of Algamal [ 3 , 19 ]. He employed the quantitative structure-activity relationship (QSAR) model to study the relationship between the biological activities IC 50 of 65 imidazo [4, 5-b] pyridine derivatives – an anticancer compound – and 15 molecular descriptors.…”
Section: Real-life Data: Algamal Datamentioning
confidence: 99%
See 1 more Smart Citation
“…The chemical dataset adopted in this study was employed in the study of Algamal [ 3 , 19 ]. He employed the quantitative structure-activity relationship (QSAR) model to study the relationship between the biological activities IC 50 of 65 imidazo [4, 5-b] pyridine derivatives – an anticancer compound – and 15 molecular descriptors.…”
Section: Real-life Data: Algamal Datamentioning
confidence: 99%
“…Batah et al [ 14 ] proposed a modified Jackknife ridge estimator by combining the ideas of the generalized ridge estimator and Jackknifed ridge estimator. Also, Algamal [ 3 ] developed the modified Jackknifed ridge gamma regression estimator. Recently, the modified version of the ridge regression estimator with two biasing parameters was proposed for both the LRM and GRM [ 15 , 16 ].…”
Section: Introductionmentioning
confidence: 99%
“…Regression models have several applications in chemometrics and other disciplines. [1][2][3][4][5] Influence diagnostics are vital to any regression modeling for testing the model reliability as it determines the strange effect of influential observations on regression model fitting. There are several methods to diagnose the influential observations in the linear regression model.…”
Section: Introductionmentioning
confidence: 99%
“…Furthermore, Månsson (2012) suggested ridge estimators for the negative binomial regression model. Recently, Amin et al (2020a) and Algamal (2018a) proposed some ridge estimators and recommended best ridge estimator for the gamma RR. Algamal (2018b) presented an efficient estimation algorithm of biasing parameter of the ridge estimator.…”
Section: Introductionmentioning
confidence: 99%