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Post-L1-Penalized Estimators in High-Dimensional Linear Regression Models
Post-L1-Penalized Estimators High-Dimensional Linear Regression Models
2010/3/9
In this paper we study the post-penalized estimator which applies ordinary,
unpenalized linear regression to the model selected by the first step penalized estimators,
typically the LASSO. It is wel...
Smoothing ℓ₁-penalized estimators for high-dimensional time-course data
Lasso Local least squares Multivariate regression Variable selection Weighted likelihood
2009/9/16
When a series of (related) linear models has to be estimated it is often appropriate to combine the different data-sets to construct more efficient estimators. We use ℓ₁-penalized estimato...