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A GRAPHICAL DIAGNOSTIC FOR VARIANCE FUNCTIONS
Author(s) -
Pardoe Iain,
Cook R. Dennis
Publication year - 2007
Publication title -
australian and new zealand journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 41
eISSN - 1467-842X
pISSN - 1369-1473
DOI - 10.1111/j.1467-842x.2007.00478.x
Subject(s) - variance function , mathematics , variance (accounting) , statistics , simple (philosophy) , bayesian probability , simple linear regression , regression , regression analysis , function (biology) , linear regression , bayesian linear regression , data mining , computer science , bayesian inference , philosophy , accounting , epistemology , evolutionary biology , business , biology
Summary This paper proposes diagnostic plots for regression variance functions. It shows how to extend graphical methodology that uses Bayesian sampling for checking the regression mean function to also check the variance function. Plots can be constructed quickly and easily for any model of interest. These plots help to identify model weaknesses and can suggest ways to make improvements. The proposed methodology is illustrated with two examples: a simple linear regression model to fix ideas, and a more complex study involving count data to demonstrate the potential for wide application.