A Non-Parametric Test of Independence

By W. Hoeffding. 1948

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

Predicting the effect of interventions using invariance principles for nonlinear models (2016, background): “There has been some progress towards nonparametric independence tests [1, 7, 2, 12, 14, 16].”
Consistent Nonparametric Tests of Independence (2010, background): “Ford = d′ = 1, an early nonparametric test for independence, due to Hoeffding (1948); Blum et al. (1961), is based 1.”
Non-linear Time Series: A Selective Review* (1994, background): “The idea of using such a functional for testing independence between two random variables X and Y in a non-time series setting goes back at least to Hoeffding (1948) and has been considered further by Blum et al.”
Multivariate Rank-Based Distribution-Free Nonparametric Testing Using Measure Transportation (2019, methodology): “In fact, RdCov2n is exactly equivalent to the statistic proposed in Blum, Kiefer, and Rosenblatt (1961) (also see the right-hand sides of Equations (15) and (16) for the population and the empirical versions, respectively), which in turn is a modified version of Hoeffding’s D-statistic.”
A Nonparametric Test of Serial Independence for Time Series and Residuals (2001, methodology): “Their work generalizes Hoeffding (1948) to serial independence.”
A Consistent Test for Bivariate Dependence (1993, unknown): “The main exception is the Ho-distribution-free rank test first proposed by Hoeffding (1948) and given later in a more transparent form by Blum, Kiefer & Rosenblatt (1961).”
A Projection-based Conditional Dependence Measure with Applications to High-dimensional Undirected Graphical Models. (2015, methodology): “Other related works include Hoeffding (1948), Blomqvist (1950), Blum et al. (1961), and some methods described in Hollander et al. (2013) and Anderson (1962).”
A New Coefficient of Correlation (2019, background): “ls to address this deciency of the classical coecients [23], such as the maximal correlation coecient [5, 15, 21, 33], various coecients based on joint cumulative distribution functions and ranks [3, 4, 8, 9, 11, 14, 18, 22, 30, 32, 35, 36, 46{49], kernel-based methods [16, 17, 31, 40, 51], informat”
A multivariate nonparametric test of independence Nail (2006, methodology): “Test decisions for Hoeffding’s independence test in this study are based on the large sample approximation nB, implemented by Frank Harrell in the R package Hmisc.”
Symmetric rank covariances: a generalized framework for nonparametric measures of dependence (2017, methodology): “Theorem 2.2 (Multivariate version of Theorem 3.1 in Hoeffding, 1948).”