A robust estimate of the correlation coefficient for bivariate normal distribution using ranked set sampling

DOI10.1016/j.jspi.2004.06.006zbMath1077.62047OpenAlexW2071077058MaRDI QIDQ2581820

Gang Zheng, Reza Modarres

Publication date: 10 January 2006

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

Full work available at URL: https://doi.org/10.1016/j.jspi.2004.06.006

zbMATH Keywords

Unbiased estimating equationPartial likelihoodModified maximum likelihood estimationSample correlation coefficientVariance-stabilizing

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Measures of association (correlation, canonical correlation, etc.) (62H20) Point estimation (62F10) Robustness and adaptive procedures (parametric inference) (62F35)

Related Items (6)

Estimation of nonparanormal graphical models based on ranked set sampling (RSS) ⋮ Pseudo maximum likelihood estimates using ranked set sampling with applications to estimating correlation ⋮ Unnamed Item ⋮ Confidence intervals for the correlation from a bivariate normal ⋮ Estimation of a parameter of Morgenstern type bivariate exponential distribution by ranked set sampling ⋮ Gumbel's bivariate exponential distribution: estimation of the association parameter using ranked set sampling

Cites Work

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• Minimax variance estimation of a correlation coefficient for \(\epsilon\)-contaminated bivariate normal distributions
• Modified maximum likelihood estimators based on ranked set samples
• The Asymptotics of Maximum Likelihood and Related Estimators Based on Type II Censored Data
• Inferences on the Correlation Coefficient in Bivariate Normal Populations From Ranked Set Samples
• Unbiased estimation of parameters by order statistics in the case of censored samples
• Concomitants and correlation estimates
• U-Statistics and imperfect ranking in ranked set sampling
• Estimation for a Common Correlation Coefficient in Bivariate Normal Distributions with Missing Observations
• Experimental Designs for Estimating the Correlation Between Two Destructively Tested Variables
• Asymptotic Properties of Non-Linear Least Squares Estimators

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