Adjusted \(R^2\) measures for the inverse Gaussian regression model
type: Item
instance of: scholarly article
title: Adjusted \(R^2\) measures for the inverse Gaussian regression model
zbMATH Open document ID: 1037.62068
author: Harald Heinzl
author: Martina Mittlböck
published in: Computational Statistics
publication date: 2004-03-16T00:00:00Z
review text: The paper presents two different definitions of the \(R^2\) measure (coefficient of determination) for the inverse Gaussian regression model. The first definition is based on deviances and the second one is based on the sums-of-squares principle. Proper adjustments for the proposed \(R^2\) measures necessary to reduce their bias are proposed and the corresponding adjusted \(R^2\) measures are investigated and compared in a simulation study. Their application is illustrated by a real medicine data example. The use of adjusted \(R^2\) measures is recommended in general.
Mathematics Subject Classification ID: 62J99
Mathematics Subject Classification ID: 62J07
zbMATH DE Number: 2058955
zbMATH Keywords: regression model
zbMATH Keywords: deviance
zbMATH Keywords: sums-of-squares
zbMATH Keywords: shrinkage
zbMATH Keywords: predictive power
zbMATH Keywords: generalized linear model
MaRDI profile type: Publication
full work available at URL: s001800200125
OpenAlex ID: W2913995823
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DOI: 10.1007/S001800200125
description: scientific article; zbMATH DE number 2058955