Results 121 to 130 of about 4,500 (154)

Reproduction capabilities of penalized hyperbolic-polynomial splines

Applied Mathematics Letters, 2022
11 pages, 2 ...
Costanza Conti, Rosanna Campagna
exaly   +6 more sources

Uniform convergence of penalized splines

Stat, 2020
Penalized splines are popular for nonparametric regression. We establish the minimax rate optimality of penalized splines for uniform convergence, thus improving the existing rate in the literature. The result is applicable to several types of penalized splines that are commonly used and holds under mild conditions on the design points.
Luo Xiao
exaly   +3 more sources

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Adaptive penalized splines for data smoothing

Computational Statistics and Data Analysis, 2017
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yongmiao Hong, Lianqiang Yang
exaly   +2 more sources

Intensity estimation on geometric networks with penalized splines

Annals of Applied Statistics, 2022
In the past decades, the growing amount of network data has lead to many novel statistical models. In this paper we consider so called geometric networks. Typical examples are road networks or other infrastructure networks. But also the neurons or the blood vessels in a human body can be interpreted as a geometric network embedded in a three ...
Marc Schneble, Göran Kauermann
exaly   +4 more sources

Asymptotic theory of penalized splines

Electronic Journal of Statistics, 2019
The paper gives a unified study of the large sample asymptotic theory of penalized splines including the O-splines using B-splines and an integrated squared derivative penalty [22], the P-splines which use B-splines and a discrete difference penalty [13], and the T-splines which use truncated polynomials and a ridge penalty [24].
Luo Xiao
exaly   +3 more sources

ON SEMIPARAMETRIC REGRESSION WITH O'SULLIVAN PENALIZED SPLINES [PDF]

Australian and New Zealand Journal of Statistics, 2008
SummaryAn exposition on the use of O'Sullivan penalized splines in contemporary semiparametric regression, including mixed model and Bayesian formulations, is presented. O'Sullivan penalized splines are similar to P‐splines, but have the advantage of being a direct generalization of smoothing splines. Exact expressions for the O'Sullivan penalty matrix
Matt Wand
exaly   +4 more sources

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

Constrained penalized splines

Canadian Journal of Statistics, 2012
AbstractThe penalized spline is a popular method for function estimation when the assumption of “smoothness” is valid. In this paper, methods for estimation and inference are proposed using penalized splines under additional constraints of shape, such as monotonicity or convexity.
openaire   +1 more source

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

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