WebJun 18, 2016 · In addition our method is more robust to heavy-tailed error distributions than the SIS since the canonical correlation is always larger than the marginal Pearson correlation (i.e., stronger signal strength relative to the noise level). This is clearly illustrated in the simulation studies. WebIn this paper we propose a robust rank correlation screening (RRCS) method to deal with ultra-high dimensional data. The new procedure is based on the Kendall $\tau$ …
The Spearman rank correlation screening for ultrahigh …
WebIndependence screening is a variable selection method that uses a ranking criterion to select significant variables, particularly for statistical models with nonpolynomial … WebIn this paper we propose a robust rank correlation screening (RRCS) method to deal with ultra-high dimensional data. The new procedure is based on the Kendall \tau correlation … doctor who and the invisible enemy
Robust feature screening for elliptical copula regression model ...
WebROBUST RANK CORRELATION BASED SCREENING 1849 a moment condition. Another rank correlation is the Spearman correlation [see, e.g., Wackerly, Mendenhall and Scheaffer (2002)]. The Spearman rank correlation coefficient is equivalent to the traditional linear correlation coefficient computed on ranks of items [Wackerly, Mendenhall and Scheaffer ... WebDec 20, 2010 · In this paper we propose a robust rank correlation screening (RRCS) method to deal with ultra-high dimensional data. The new procedure is based on the Kendall \tau … WebMay 1, 2024 · Zhu et al. (2011) proposed a sure independent ranking and screening procedure for most generalized parametric or semiparametric models. Li et al. (2012a) presented a robust rank correlation screening procedure, which is applicable to transformation regression models and single-index models. extraplanetary civilizations