Krivobokova T, Crainiceanu CM, Kauermann G. Fast adaptive penalized splines. JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS. 2008;17(1):1-20.This article proposes a numerically simple method for locally adaptive smoothing. The heterogeneous regression function is modeled as a penalized spline with a varying smoothing parameter modeled as another penalized spline. This is formulated as a hierarchical mixed model, with spline coefficients following zero mean normal distribution with a smooth variance structure. The major contribution of this article is to use the Laplace approximation of the marginal likelihood for estimation. This method is numerically simple and fast. The idea is extended to spatial and non-normal response smoothing
We propose a new method to find spatially adaptive smoothing splines. This new method breaks down th...
AbstractThis paper introduces a new nonparametric estimator based on penalized regression splines fo...
A new computational algorithm for estimating the smoothing parameters of a multidimensional penalize...
This paper proposes a numerically simple method for locally adaptive smooth-ing. The heterogeneous r...
This paper proposes a numerically simple routine for locally adaptive smoothing. The locally heterog...
An increasingly popular tool for nonparametric smoothing are penalized splines (P-splines) which use...
We propose a new adaptive penalty for smoothing via penalized splines. The new form of adaptive pena...
We propose a new adaptive penalty for smoothing via penalized splines. The new form of adaptive pena...
This paper considers the development of spatially adaptive smoothing splines for the esti-mation of ...
This paper considers the development of spatially adaptive smoothing splines for the esti-mation of ...
We consider the applicability of smoothing splines via the penalized likelihood method to large data...
We use a reproducing kernel Hilbert space representation to derive the smoothing spline solution whe...
We propose the generalized profiling method to estimate the multiple regression functions in the fra...
We use a reproducing kernel Hilbert space representation to derive the smoothing spline solution whe...
Krivobokova T. Theoretical and practical aspects of penalized spline smoothing. Bielefeld (Germany):...
We propose a new method to find spatially adaptive smoothing splines. This new method breaks down th...
AbstractThis paper introduces a new nonparametric estimator based on penalized regression splines fo...
A new computational algorithm for estimating the smoothing parameters of a multidimensional penalize...
This paper proposes a numerically simple method for locally adaptive smooth-ing. The heterogeneous r...
This paper proposes a numerically simple routine for locally adaptive smoothing. The locally heterog...
An increasingly popular tool for nonparametric smoothing are penalized splines (P-splines) which use...
We propose a new adaptive penalty for smoothing via penalized splines. The new form of adaptive pena...
We propose a new adaptive penalty for smoothing via penalized splines. The new form of adaptive pena...
This paper considers the development of spatially adaptive smoothing splines for the esti-mation of ...
This paper considers the development of spatially adaptive smoothing splines for the esti-mation of ...
We consider the applicability of smoothing splines via the penalized likelihood method to large data...
We use a reproducing kernel Hilbert space representation to derive the smoothing spline solution whe...
We propose the generalized profiling method to estimate the multiple regression functions in the fra...
We use a reproducing kernel Hilbert space representation to derive the smoothing spline solution whe...
Krivobokova T. Theoretical and practical aspects of penalized spline smoothing. Bielefeld (Germany):...
We propose a new method to find spatially adaptive smoothing splines. This new method breaks down th...
AbstractThis paper introduces a new nonparametric estimator based on penalized regression splines fo...
A new computational algorithm for estimating the smoothing parameters of a multidimensional penalize...