Box-Cox transformations in linear models: Large sample theory and tests of normality

DOI10.2307/3315946zbMath1012.62072OpenAlexW2008765054MaRDI QIDQ4801369

Richard A. Lockhart, Gemai Chen, Michael A. Stephens

Publication date: 24 June 2003

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://semanticscholar.org/paper/45671be5ebd851de8f95d4dc3b17fa15595cb7c8

zbMATH Keywords

maximum likelihood estimationnonlinear regressionempirical distribution functionsgoodness of fittransformation to normality

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Parametric tolerance and confidence regions (62F25) Asymptotic distribution theory in statistics (62E20) Linear regression; mixed models (62J05) Order statistics; empirical distribution functions (62G30)

Related Items (12)

What is a statistical model? (With comments and rejoinder). ⋮ Transformations to symmetry based on the probability weighted characteristic function ⋮ Thinking outside the box: Statistical inference based on Kullback-Leibler empirical projections ⋮ Optimal asymmetric kernels ⋮ Estimating the error distribution in semiparametric transformation models ⋮ Automatic robust Box-Cox and extended Yeo-Johnson transformations in regression ⋮ Estimation of the error density in a semiparametric transformation model ⋮ A DIFFUSION MODEL FOR ELECTRICITY PRICES ⋮ The Box-Cox transformation: review and extensions ⋮ Tests for validity of the semiparametric heteroskedastic transformation model ⋮ Efficiency of t-Test and Hotelling's T ²-Test After Box-Cox Transformation ⋮ The p-value Function and Statistical Inference

Uses Software

• MINITAB

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• The empirical distribution function of residuals from generalised regression
• Asymptotic results for goodness-of-fit statistics with unknown parameters
• Weak convergence of the empirical process of residuals in linear models with many parameters
• The Analysis of Transformed Data
• Statistical Tests Based on Transformed Data
• Power transformations to symmetry
• Measures of Location of Skew Distributions Obtained Through Box-Cox Transformations
• The Large-Sample Behavior of Transformations to Normality
• An Analysis of Transformations Revisited
• Confidence intervals following Box‐Cox transformation
• An Analysis of Transformations Revisited, Rebutted
• Computing the distribution of quadratic forms in normal variables
• Convergence of stochastic processes

This page was built for publication: Box-Cox transformations in linear models: Large sample theory and tests of normality