Speaker
Description
In standard regression models, pairs of covariates and response variables are observed. In the more complex case of shuffled regression (on anonymized data), we only observe a sample of covariates on the one hand, and a sample of responses on the other, but we don't know which response corresponds to each covariate. In the even more complex case where responses and covariates are not necessarily measured on the same individuals, both samples of covariates and responses are still observed, but there is not necessarily a link between them. The data are unlinked. This raises the question of whether the link between the two samples in the shuffled case provides any real information compared with the unlinked case, i.e. whether or not the optimal rates of convergence of estimators are identical in the two models. We provide some answers to this question.
