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SEMIPARAMETRIC PENALIZED SPLINE REGRESSION
SEMIPARAMETRIC PENALIZED SPLINE REGRESSIONIn 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.
吉田, 拓真 +5 more
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Penalized spline estimator with multi smoothing parameters in bi-response multi-predictor nonparametric regression model for longitudinal data [PDF]
Songklanakarin Journal of Science and Technology (SJST), 2020 Penalized spline estimators that depend on a smoothing parameter is one type of estimator used in the estimation regression curve in nonparametric regression.
Anna Islamiyati, Fatmawati, Nur Chamidah
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Use of Two Smoothing Parameters in Penalized Spline Estimator for Bi-variate Predictor Non-parametric Regression Model [PDF]
Journal of Sciences, Islamic Republic of Iran, 2020 Penalized spline criteria involve the function of goodness of fit and penalty, which in the penalty function contains smoothing parameters. It serves to control the smoothness of the curve that works simultaneously with point knots and spline degree. The
Anna Islamiyati
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Penalized regression splines in Mixture Density Networks
The International Journal of Biostatistics, 2022 Abstract Mixture Density Networks (MDN) belong to a class of models that can be applied to data which cannot be sufficiently described by a single distribution since it originates from different components of the main unit and therefore needs to be described by a mixture of densities.
Seifert, Quentin Edward +6 more
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Penalized spline models and applications [PDF]
Penalized spline regression models are a popular statistical tool for curve fitting\ud problems due to their flexibility and computational efficiency. In particular, penalized\ud cubic spline functions have received a great deal of attention.
Costa, Maria J. (Maria João)
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Estimating conditional heteroscedastic nonlinear autoregressive model by using smoothing spline and penalized spline methods [PDF]
Songklanakarin Journal of Science and Technology (SJST), 2019 We propose smoothing spline (SS) and penalized spline (PS) methods in a class of nonparametric regression methods for estimating the unknown functions in a conditional heteroscedastic nonlinear autoregressive (CHNLAR) model.
Autcha Araveeporn
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Estimasi Model Regresi Spline Kubik Tersegmen dengan Metode Penalized Least Square
Al-Khwarizmi: Jurnal Pendidikan Matematika dan Ilmu Pengetahuan Alam, 2022 : Nonparametric regression is used for data whose data pattern is non-parametric. One of the estimators that can be developed is a segmented cubic spline which is able to show several segmentation changes in the data.
Anna Islamiyati +6 more
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APPLICATION OF PENALIZED SPLINE-SPATIAL AUTOREGRESSIVE MODEL TO HIV CASE DATA IN INDONESIA
Barekeng, 2023 Spatial regression analysis is a statistical method used to perform modeling by considering spatial effects. Spatial models generally use a parametric approach by assuming a linear relationship between explanatory and response variables.
Nindi Pigitha +2 more
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Fast Adaptive Penalized Splines
Journal of Computational and Graphical Statistics, 2008 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 ...
Krivobokova, Tatyana +2 more
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Parametrization and penalties in spline models with an application to survival analysis [PDF]
, 2008 A simple parametrization, built from the definition of cubic splines, is shown to facilitate the implementation and interpretation of penalized spline models, whatever configuration of knots is used.
Costa, Maria J. (Maria João) +1 more
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