Robust approach for comparing two dependent normal populations through Wald-type tests based on Rényi’s pseudodistance estimators

被引：0
作者：
Elena Castilla
María Jaenada
Nirian Martín
Leandro Pardo
机构：
[1] Rey Juan Carlos University,Department of Applied Mathematics, Materials Science and Engineering, and Electronic Technology
[2] Complutense University of Madrid,Department of Statistics and Operations Research
[3] Complutense University of Madrid,Department of Financial and Actuarial Economics and Statistics
来源：
Statistics and Computing | 2022年 / 32卷
关键词：
Correlation test; Influence function; Rényi pseudodistance; Robustness; Wald-type test;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Since the two seminal papers by Fisher (Biometrika 10:507–521, 1915; Metron 1:1–32, 1921) were published, the test under a fixed value correlation coefficient null hypothesis for the bivariate normal distribution constitutes an important statistical problem. In the framework of asymptotic robust statistics, it remains being a topic of great interest to be investigated. For this and other tests, focused on paired correlated normal random samples, Rényi’s pseudodistance estimators are proposed, their asymptotic distribution is established and an iterative algorithm is provided for their computation. From them the Wald-type test statistics are constructed for different problems of interest and their influence function is theoretically studied. For testing null correlation in different contexts, an extensive simulation study and two real data based examples support the robust properties of our proposal.
引用
收藏
相关论文
共 39 条
[1]  
Basak S(2021)On the optimal density power divergence tuning parameter J. Appl. Stat. 48 536-556
[2]  
Basu A(1977)Minimum Hellinger distance estimates for parametric models Ann. Stat. 5 445-463
[3]  
Jones MC(1961)Decomposable pseudodistances and applications in statistical estimation J. Stat. Plan. Inference 142 2574-2585
[4]  
Beran R(1982)The influence function and its application to data validation Am. J. Math. Manag. Sci. 2 263-288
[5]  
Broniatowski M(1975)Robust estimation and outlier detection with correlation coefficients Biometrika 62 531-545
[6]  
Toma A(1915)Frequency-distribution of the values of the correlation coefficient in samples from an indefinitely large population Biometrika 10 507-521
[7]  
Vajda I(1921)On the “probable error” of a coefficient of correlation deduced from a small sample Metron 1 1-32
[8]  
Chernick MR(2008)Robust parameter estimation with a small bias against contamination J. Multivar. Anal. 99 2053-2081
[9]  
Devlin SJ(1940)On samples from a normal bivariate population Ann. Math. Stat. 11 410-426
[10]  
Gnanadesikan R(2019)A robust Pearson correlation test for a general point null using a surrogate bootstrap distribution PLoS ONE 14 e0216287-186
1234