Accurate confidence intervals in regression analyses of non-normal data
DOI10.1007/s10463-006-0085-1zbMath1184.62045OpenAlexW2108232773MaRDI QIDQ1039838
Publication date: 23 November 2009
Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10463-006-0085-1
bootstrapkurtosisskewnessEdgeworth expansionCornish-Fisher transformationCharlier differential seriesone-sample \(t\)
Estimation in multivariate analysis (62H12) Parametric tolerance and confidence regions (62F25) Asymptotic distribution theory in statistics (62E20) Linear regression; mixed models (62J05) Bootstrap, jackknife and other resampling methods (62F40)
Related Items (2)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Edgeworth expansion for Student's t statistic under minimal moment conditions
- Inverting an Edgeworth expansion
- Edgeworth expansions for bootstrapping regression models
- Edgeworth expansion in regression models
- Unusual properties of bootstrap confidence intervals in regression problems
- Normalizing transformations and bootstrap confidence intervals
- A local parameterization of orthogonal and semi-orthogonal matrices with applications
- Robust regression: Asymptotics, conjectures and Monte Carlo
- Asymptotic expansion of the null distribution of test statistic for linear hypothesis in nonnormal linear model
- Edgeworth expansions for the conditional distributions in logistic regression models
- Higher order normalizing transformations of asymptotic \(U\)-statistics for removing bias, skewness and kurtosis
- Statistical Analysis of Financial Data in S-Plus
- Asymptotic Approximations to Distributions
- RELAXING ASSUMPTIONS IN THE ONE SAMPLE t-TEST
- Relation between the shape of population distribution and the robustness of four simple test statistics
- The Distribution of the t-Statistic under Non-Normality
- Modified t Tests and Confidence Intervals for Asymmetrical Populations
- The robustness of the one-samplet-test over the pearson system
- Accurate confidence limits for scalar functions of vector M-estimands
- Bootstrapping and empirical edgeworth expansions in multiple linear regression models
- Generalized Asymptotic Expansions of Cornish-Fisher Type
- TESTING FOR NORMALITY
- THE DISTRIBUTION OF ‘STUDENT'S’ t IN RANDOM SAMPLES OF ANY SIZE DRAWN FROM NON-NORMAL UNIVERSES
- The Approximate Distribution of Student's Statistic
- The bootstrap and Edgeworth expansion
This page was built for publication: Accurate confidence intervals in regression analyses of non-normal data