5 citations · 8 across the 5 of their papers we have counts for
5 papers
A generalized distance covariance framework for genome-wide association studies
Dominic Edelmann, Fernando Castro-Prado, Jelle J. Goeman
When testing for the association of a single SNP with a phenotypic response, one usually considers an additive genetic model, assuming that the mean of of the response for the hete…
Nonparametric independence tests in high-dimensional settings, with applications to the genetics of complex disease
Fernando Castro-Prado
[PhD thesis of FCP.] Nowadays, genetics studies large amounts of very diverse variables. Mathematical statistics has evolved in parallel to its applications, with much recent inter…
Tests for categorical data beyond Pearson: A distance covariance and energy distance approach
Fernando Castro-Prado, Wenceslao González-Manteiga, Javier Costas +2
Categorical variables are of uttermost importance in biomedical research. When two of them are considered, it is often the case that one wants to test whether or not they are stati…
Testing for genetic interactions in complex disease with distance correlation
Fernando Castro-Prado, Javier Costas, Dominic Edelmann +2
Understanding epistasis (genetic interaction) may shed some light on the genomic basis of common diseases, including disorders of maximum interest due to their high socioeconomic b…
Nonparametric independence tests in metric spaces: What is known and what is not
Fernando Castro-Prado, Wenceslao González-Manteiga
Distance correlation is a recent extension of Pearson's correlation, that characterises general statistical independence between Euclidean-space-valued random variables, not only l…