Diagnostic power of some graphical methods in geometric regression model addressing cervical cancer data

Diagnostic power of some graphical methods in geometric regression model addressing cervical cancer data

In the framework of generalized linear models (GLM), this paper explores the design and applicability of partial residual (PRES), augmented partial residual (APRES), and conditional expectation and residuals (CERES) plots for visualizing an outlier's diagnostics as a function of selected variab...

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Bibliographic Details
Main Authors: Zawar Hussain, Atif Akbar, Mohammed M. A. Almazah, A. Y. Al-Rezami, Fuad S. Al-Duais
Format: Article
Language:English
Published: AIMS Press 2024-01-01
Series:AIMS Mathematics
Subjects:
visual impression
geometric regression
diagnostics
predictors transformations
cervical cancer
Online Access:https://www.aimspress.com/article/doi/10.3934/math.2024198?viewType=HTML

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https://www.aimspress.com/article/doi/10.3934/math.2024198?viewType=HTML

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