Ontology highlight
ABSTRACT:
SUBMITTER: Maclehose RF
PROVIDER: S-EPMC3631538 | biostudies-literature | 2010 Jun
REPOSITORIES: biostudies-literature
Biometrics 20090608 2
High-dimensional and highly correlated data leading to non- or weakly identified effects are commonplace. Maximum likelihood will typically fail in such situations and a variety of shrinkage methods have been proposed. Standard techniques, such as ridge regression or the lasso, shrink estimates toward zero, with some approaches allowing coefficients to be selected out of the model by achieving a value of zero. When substantive information is available, estimates can be shrunk to nonnull values; ...[more]