Sequential learning of regression models by penalized estimation

Wessel N. van Wieringen & Harald Binder
When data arrive in a sequence of two or more data sets, modeling on the most recent data set should take previous data sets into account. We specifically investigate a strategy for regression modeling when parameter estimates from previous data can be used as anchoring points, yet may not be available for all parameters, thus covariance information cannot be reused. A procedure that updates through targeted penalized estimation, which shrinks the estimator towards a nonzero...
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