Results 11 to 20 of about 15,886 (254)
S-estimation for penalized regression splines. [PDF]
SSRN Electronic Journal, 2008 This paper is about S-estimation for penalized regression splines. Penalized regression splines are one of the currently most used methods for smoothing noisy data. The estimation method used for fitting such a penalized regression spline model is mostly
Claeskens, Gerda +3 more
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Penalized hyperbolic-polynomial splines [PDF]
Applied Mathematics Letters, 2021 Splines and spline approximations using penality functions are especially useful tools in univariate approximation theory when univariate data are to be approximated, and when no interpolation property is needed. The methods using piecewise polynomial splines and penalty methods can be formulated via square (or otherwise, other \(L^p\)-norms are ...
Rosanna Campagna, Costanza Conti
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Marginal longitudinal semiparametric regression via penalized splines. [PDF]
Stat Probab Lett, 2010 We study the marginal longitudinal nonparametric regression problem and some of its semiparametric extensions. We point out that, while several elaborate proposals for efficient estimation have been proposed, a relative simple and straightforward one, based on penalized splines, has not. After describing our approach, we then explain how Gibbs sampling
Kadiri MA, Carroll RJ, Wand MP.
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SEMIPARAMETRIC PENALIZED SPLINE REGRESSION [PDF]
Bulletin of informatics and cybernetics, 2012 In this paper, we propose a new semiparametric regression estimator by using a hybrid technique of a parametric approach and a nonparametric penalized spline method. The overall shape of the true regression function is captured by the parametric part, while its residual is consistently estimated by the nonparametric part.
Yoshida, Takuma, Naito, Kanta
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Dynamic Penalized Splines for Streaming Data
Statistica Sinica, 2022 Summary: We propose a dynamic version of the penalized spline regression designed for streaming data that allows for the insertion of new knots dynamically based on sequential updates of the summary statistics. A new theory using direct functional methods rather than the traditional matrix analysis is developed to attain the optimal convergence rate in
Xue, Dingchuan, Yao, Fang
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Modeling latent spatio-temporal disease incidence using penalized composite link models.
PLoS ONE, 2022 Epidemiological data are frequently recorded at coarse spatio-temporal resolutions to protect confidential information or to summarize it in a compact manner.
Dae-Jin Lee +3 more
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Bi-Smoothed Functional Independent Component Analysis for EEG Artifact Removal
Mathematics, 2021 Motivated by mapping adverse artifactual events caused by body movements in electroencephalographic (EEG) signals, we present a functional independent component analysis based on the spectral decomposition of the kurtosis operator of a smoothed principal
Marc Vidal +2 more
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Mathematics, 2020 Rock art paintings present high sensitivity to light, and an exhaustive evaluation of the potential color degradation effects is essential for further conservation and preservation actions on these rock art systems.
Gabriel Riutort-Mayol +3 more
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Semiparametric Additive Beta Regression Models
Revstat Statistical Journal, 2021 In this paper, we study a semiparametric additive beta regression model using a parameterization based on the mean and a dispersion parameter. This model is useful for situations where the response variable is continuous and restricted to the unit ...
Germán Ibacache-Pulgar +2 more
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LASSO type Penalized Spline Regression for Binary Data [PDF]
BMC Medical Research Methodology, 2020 Abstract Background: Generalized linear mixed models (GLMMs), typically used for analyzing correlated data, can also be used for smoothing by considering the knot coefficients from a regression spline as random effects. The resulting models are called semiparametric mixed models (SPMMs).
Muhammad Abu Shadeque Mullah +2 more
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