Smoothing splines are one of the most popular approaches to nonparametric regression. Wahba (1978,1983) showed that smoothing splines are also Bayes estimates and used the corresponding prior model to derive interval estimates for the regression function. Although the interval estimates work well on a global basis, they can have poor local properties. The source of this problem is the use of a ...

To resolve the conflict between our desire for a good smoothing effect and desire to give additional weight to the recent change, a grey accumulating generation operator that can smooth the random interference of data is introduced into the double exponential smoothing method. The results of practical numerical examples have demonstrated that the proposed grey double exponential smoothing metho...

There are two popular smoothing parameter selection methods for spline smoothing. First, smoothing parameters can be estimated minimizing criteria that approximate the average mean squared error of the regression function estimator. Second, the maximum likelihood paradigm can be employed, under the assumption that the regression function is a realization of some stochastic process. In this arti...

The (cubic) smoothing spline, of Schoenberg [S64] and Reinsch [R67], [R71], has become the most commonly used spline, particularly after the introduction of generalized cross validation by Craven and Wahba [CW79] for an automatic choice of the smoothing parameter. It is the purpose of this note to derive the computational details, in terms of B-splines, for the construction of the weighted smoo...

This paper provides for the first time some computable smoothing functions for variational inequality problems with general constraints. This paper proposes also a new version of the smoothing Newton method and establishes its global and superlinear (quadratic) convergence under conditions weaker than those previously used in the literature. These are achieved by introducing a general definitio...

This study examines whether analyst coverage affects the informativeness of income smoothing. I find that income smoothing enhances earnings informativeness more greatly for firms with high analyst coverage than for firms with low analyst coverage. The results suggest that income smoothing more efficiently communicates private information to investors when firms are followed by more analysts, c...