The current multiple regression class does a QR decomposition on the complete data set. This necessitates the loading incore of the complete dataset. For large datasets, or large datasets and a requirement to do datamining or stepwise regression this is not practical. There are techniques which form the normal equations on the fly, as well as ones which form the QR decomposition on an update basis. I am proposing, first, the specification of an "UpdatingLinearRegression" interface which defines basic functionality all such techniques must fulfill.
Related to this 'updating' regression, the results of running a regression on some subset of the data should be encapsulated in an immutable object. This is to ensure that subsequent additions of observations do not corrupt or render inconsistent parameter estimates. I am calling this interface "RegressionResults".
Once the community has reached a consensus on the interface, work on the concrete implementation of these techniques will take place.