A New Function for Robust Linear Regression: An Iterative Approach
نویسنده
چکیده
In this paper, we consider solving the robust linear regression problem. We show that IRLS and Newton method can each be combined with preconditioned conjugate gradient least squares method to solve large, sparse, rectangular systems of linear, algebraic equations eeciently. We deene a new function that leads to a cheap preconditioner. Further, for this function, we show that the upper bound on the condition number of the preconditioned matrix is independent of the conditioning of the data matrix (is determined by a predeened constant). We give numerical results that demonstrate the eeectiveness of preconditioners based on this function.
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