qad : An R‐package to detect asymmetric and directed dependence in bivariate samples

作者：Florian Griessenberger, Wolfgang Trutschnig, Robert R. Junker · 发表于：Methods in Ecology and Evolution · 年份：2022 · DOI：10.1111/2041-210x.13951 · 被引用次数：9 · 研究领域：Ecology and Vegetation Dynamics Studies、Species Distribution and Climate Change、Ecosystem dynamics and resilience

Abstract Correlations belong to the standard repertoire of ecologists for quantifying the strength of dependence between two random variables. Classical dependence measures are usually not capable of detecting non‐monotonic or non‐functional dependencies. Furthermore, they completely fail to detect asymmetry and direction in dependence, which exist in many situations and should not be ignored. In this paper, we present qad (short for quantification of asymmetric dependence ), a nonparametric statistical method to quantify directed and asymmetric dependence of bivariate samples. Qad is applicable in general (e.g. linear, non‐linear, or non‐monotonic) situations, is sensitive to noise in data, exhibits a good small sample performance, detects asymmetry in dependence, shows high power in testing for independence, requires no assumptions regarding the underlying distribution of the data and reliably quantifies the information gain/predictability of quantity Y given knowledge of quantity X , and vice versa (i.e. q ( X , Y ) q ( Y , X )). Here, we briefly recall the methodology underlying qad , introduce the functions of the R‐package qad , which returns estimates for the measures denoting the directed dependence of on (or, equivalently, the influence of on ), the directed dependence of on , the asymmetry in dependence. Furthermore, qad can be used to predict Y given knowledge of X , and vice versa. Additionally, we compare empirical performance of qad with that of seven other well...