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

2006 ◽  
Vol 136 (1) ◽  
pp. 298-309 ◽  
Author(s):  
Gang Zheng ◽  
Reza Modarres
1978 ◽  
Vol 15 (2) ◽  
pp. 304-308 ◽  
Author(s):  
Warren S. Martin

Distortion in the Pearson product moment correlation due to a restricted number of scale points is evaluated in two ways. First, a simulation of the bivariate normal distribution is used to estimate the effects of varying the number of scale points on the product moment correlation. This procedure demonstrates a substantial amount of information loss. Second, other correlation coefficients and some methods to correct for this loss are discussed and related to the simulation data.


2017 ◽  
Vol 46 (3-4) ◽  
pp. 99-105
Author(s):  
Georgy Shevlyakov ◽  
Nikita Vasilevskiy

Performance of the Linfoot's informational correlation coefficient is experimentally studied at the bivariate normal distribution. It is satisfactory in the case of a strong correlation and on large samples. To reduce the bias of estimation, a symmetric version of this correlation measure is proposed. On small and large samples, this modified informational correlation coefficient outperforms Linfoot's correlation measure at the bivariate normal distribution in the wide range of the correlation coefficient.


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