Smoothing Spline Gaussian Regression: More Scalable Computation via Efficient Approximation
平滑样条高斯回归：通过有效近似实现更可扩展的计算
Summary Smoothing splines via the penalized least squares method provide versatile and effective nonparametric models for regression with Gaussian responses. The computation of smoothing splines is generally of the order O(n3), n being the sample size, which severely limits its practical applicability. We study more scalable computation of smoothing spline regression via certain low dimensional approximations that are asymptotically as efficient. A simple algorithm is…