Checking Normality and Homoscedasticity in the General Linear Model Using Diagnostic Plots

Inference for the general linear model makes several assumptions, including independence of errors, normality, and homogeneity of variance. Departure from the latter two of these assumptions may indicate the need for data transformation or removal of outlying observations. Informal procedures such a...

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Vydáno v:	Communications in statistics. Simulation and computation Ročník 41; číslo 2; s. 141 - 154
Hlavní autoři:	Schützenmeister, A., Jensen, U., Piepho, H.-P.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Colchester Taylor & Francis Group 01.02.2012 Taylor & Francis Taylor & Francis Ltd
Témata:	62-09 62J5 Approximation Computer simulation Constant residual variance Correlation Diagnostic systems Distribution theory Exact sciences and technology Homogeneity Linear inference, regression Mathematics Model checking Monte Carlo Multiplicity Multivariate analysis Normality Numerical analysis Numerical analysis. Scientific computation Numerical methods in probability and statistics Probability and statistics Residual plot Sciences and techniques of general use Simulation Simultaneous tolerance band Statistics Tolerance interval Tolerance region Tolerances Transformations Correlation Generalized linear model Statistical distribution Error estimation Data transformation Gaussian distribution Non parametric estimation Multivariate analysis Stochastic method Constant residual variance Linear model Variance Tolerance interval Outlier Statistical test Monte Carlo Multiplicity Model checking Approximation theory 62F25 Monte Carlo method Discriminant analysis Covariance analysis Independence Probability Tolerance Statistical association Statistical estimation Algorithm Variance analysis Heteroscedasticity Confidence interval Statistical method Statistical regression Diagnostic techniques Residual plot Numerical analysis Non normality Simulation Simultaneous tolerance band Correlation analysis Tolerance region Normality test Numerical simulation Computing method
ISSN:	0361-0918, 1532-4141
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