Robustness of ranking and selection rules using generalised \(g\)-and-\(k\) distributions

DOI10.1016/S0378-3758(97)00050-5zbMath0955.62017OpenAlexW2054030090MaRDI QIDQ1378762

Michele A. Haynes, H. L. MacGillivray, Kerrie L. Mengersen

Publication date: 27 February 2001

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0378-3758(97)00050-5

zbMATH Keywords

robustnessfrequentist selection ruleg-and-h distributionsg-and-k distributions

Mathematics Subject Classification ID

Robustness and adaptive procedures (parametric inference) (62F35) Asymptotic properties of parametric tests (62F05)

Related Items (12)

A restricted subset selection procedure for selecting the largest normal mean under heteroscedasticity ⋮ Approximate Bayesian computation by modelling summary statistics in a quasi-likelihood framework ⋮ A transdimensional approximate Bayesian computation using the pseudo-marginal approach for model choice ⋮ Parameter estimation of Tukey-type distributions: A comparative analysis ⋮ Bayesian modelling of skewness and kurtosis with two-piece scale and shape distributions ⋮ Quantile-distribution functions and their use for classification, with application to naïve Bayes classifiers ⋮ Discrepancy-based inference for intractable generative models using quasi-Monte Carlo ⋮ Generalized Control Charts for Non-Normal Data Usingg-and-kDistributions ⋮ Bayesian estimation of \(g\)-and-\(k\) distributions using MCMC ⋮ Local dimension reduction of summary statistics for likelihood-free inference ⋮ A simple approach to the estimation of Tukey's gh distribution ⋮ Weighted quantile-based estimation for a class of transformation distributions.

Uses Software

• RANKSEL

Cites Work

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• On selecting a subset containing the population with the smallest variance
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• A Single-Sample Multiple Decision Procedure for Ranking Variances of Normal Populations

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