Estimating kurtosis and confidence intervals for the variance under nonnormality

DOI10.1080/00949655.2013.840628zbMath1453.62423OpenAlexW2027359106MaRDI QIDQ5219525

Brent D. Burch

Publication date: 12 March 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2013.840628

zbMATH Keywords

bootstrapinterval estimationlarge-sample theory

Mathematics Subject Classification ID

Parametric tolerance and confidence regions (62F25) Asymptotic distribution theory in statistics (62E20)

Related Items (4)

High frequency trading and stock index returns: a nonlinear dynamic analysis ⋮ Distribution-dependent and distribution-free confidence intervals for the variance ⋮ Robust confidence intervals for the difference of two independent population variances ⋮ Bootstrap lower confidence limits of superstructure process capability indices for Esscher-transformed Laplace distribution

Uses Software

• bootlib

Cites Work

• Nonparametric bootstrap confidence intervals for variance components applied to interlaboratory comparisons
• One-sided confidence intervals for population variances of skewed distributions
• Approximate confidence interval for standard deviation of nonnormal distributions
• Nonparametric confidence intervals for population variance of one sample and the difference of variances of two samples
• Improving the performance of kurtosis estimator
• Assessing the performance of normal-based and REML-based confidence intervals for the intraclass correlation coefficient
• Interval Estimation for the Difference of Two Independent Variances
• Better Bootstrap Confidence Intervals
• Robust confidence interval for the variance
• Improved Large-Sample Confidence Intervals for Ratios of Variance Components in Nonnormal Distributions
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