This question and its answer might highlight my naivete regarding Brownian/distance correlation.
I'm using the difference between a matrix of distance correlations, as calculated by
energy::dcor(), and absolute value Pearson correlations, as calculated by
cor(), to highlight potential nonlinear dependencies introduced with a certain estimation technique.
In my resulting difference matrix, I have a handful of negative values indicating that the Pearson correlation is larger in magnitude than the distance correlation (range from
First, is my approach adequate? If so, how do I explain why the Pearson correlations might be larger in magnitude than distance correlation?