— We propose the Multiresponse Sparse Regression algorithm, an input selection method for the purpose of estimating several response variables. It is a forward selection procedur...
In this paper, we develop algorithms for robust linear regression by leveraging the connection between the problems of robust regression and sparse signal recovery. We explicitly ...
The Total Least Squares method is generalized in the context of the functional linear model. A smoothing splines estimator of the functional coefficient of the model is first prop...
Simulation experiments are often analyzed through a linear regression model of their input/output data. Such an analysis yields a metamodel or response surface for the underlying ...
It is widely believed that program analysis can be more closely targeted to the needs of programmers if the program is accompanied by further redundant documentation. This may inc...