Conditional dependence learning with high-dimensional conditioning variables.Jianxin Bi,Xingdong Feng&Jingyuan Liu.Abstract Conditional dependence plays a crucial role in various statistical procedures,including v...Conditional dependence learning with high-dimensional conditioning variables.Jianxin Bi,Xingdong Feng&Jingyuan Liu.Abstract Conditional dependence plays a crucial role in various statistical procedures,including variable selection,network analysis and causal inference.However,there remains a paucity of relevant research in the context of high-dimensional conditioning variables,a common challenge encountered in the era of big data.To address this issue,many existing studies impose certain model structures,yet high-dimensional conditioning variables often introduce spurious correlations in these models.In this paper,we systematically study the estimation biases inherent in widely-used measures of conditional dependence when spurious variables are present under high-dimensional settings.展开更多
文摘Conditional dependence learning with high-dimensional conditioning variables.Jianxin Bi,Xingdong Feng&Jingyuan Liu.Abstract Conditional dependence plays a crucial role in various statistical procedures,including variable selection,network analysis and causal inference.However,there remains a paucity of relevant research in the context of high-dimensional conditioning variables,a common challenge encountered in the era of big data.To address this issue,many existing studies impose certain model structures,yet high-dimensional conditioning variables often introduce spurious correlations in these models.In this paper,we systematically study the estimation biases inherent in widely-used measures of conditional dependence when spurious variables are present under high-dimensional settings.
