Results 241 to 250 of about 15,886 (254)

Bivariate Penalized Splines for Regression

Statistica Sinica, 2013
In this paper the asymptotic behavior of penalized spline estimators is studied using bivariate splines over triangulations and an energy functional as the penalty. The rate of L2 convergence is derived, which achieves the optimal nonparametric convergence rate established by Stone (1982).
Ming-Jun Lai, Li Wang
openaire   +1 more source

On the asymptotics of penalized splines

Biometrika, 2008
SUMMAvRY We study the asymptotic behaviour of penalized spline estimators in the univariate case. We use B-splines and a penalty is placed on mth-order differences of the coefficients. The number of knots is assumed to converge to infinity as the sample size increases. We show that penalized splines behave similarly to Nadaraya-Watson kernel estimators
Yingxing Li, David Ruppert
openaire   +2 more sources

Penalized I-spline monotone regression estimation

Communications in Statistics - Simulation and Computation, 2019
We propose a penalized regression spline estimator for monotone regression. To construct the estimator, we adopt the I-splines with the total variation penalty.
Junsouk Choi, JungJun Lee, Jae-Hwan Jhong, Ja-Yong Koo   +3 more
openaire   +1 more source

Penalized Splines and Reproducing Kernel Methods

The American Statistician, 2006
Two data analytic research areas—penalized splines and reproducing kernel methods—have become very vibrant since the mid-1990s. This article shows how the former can be embedded in the latter via theory for reproducing kernel Hilbert spaces. This connection facilitates cross-fertilization between the two bodies of research.
Pearce, N.D., Wand, M.P.
openaire   +2 more sources

Adaptive penalized splines for data smoothing

Computational Statistics & Data Analysis, 2017
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lianqiang Yang, Yongmiao Hong
openaire   +1 more source

Penalized Estimation of Free-Knot Splines

Journal of Computational and Graphical Statistics, 1999
Abstract Polynomial splines are often used in statistical regression models for smooth response functions. When the number and location of the knots are optimized, the approximating power of the spline is improved and the model is nonparametric with locally determined smoothness.
openaire   +1 more source

Deconvolution density estimation using penalized splines

Journal of Statistical Planning and Inference
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jing, Hanxiao, Meyer, Mary C., Sun, Jiayang   +2 more
openaire   +1 more source

Dielectric function parameterization by penalized splines

SPIE Proceedings, 2017
In this article, we investigate the penalized spline (P-spline) approach to restrict flexibility of dielectric function parameterization by B-splines and prevent overfitting of the ellipsometric data. The penalty degree is easily controlled by a certain smoothing parameter.
openaire   +1 more source

Penalized Splines

2018
Jaroslaw Harezlak, David Ruppert, Matt P. Wand   +2 more
openaire   +1 more source

Penalized Splines and Multilevel Models

2013
Göran Kauermann, Torben Kuhlenkasper
openaire   +1 more source