Results 11 to 20 of about 125,587 (258)

Smoothing and Differentiation of Kinematic Data Using Functional Data Analysis Approach: An Application of Automatic and Subjective Methods

Applied Sciences, 2020
Smoothing is one of the fundamental procedures in functional data analysis (FDA). The smoothing parameter λ influences data smoothness and fitting, which is governed by selecting automatic methods, namely, cross-validation (CV) and generalized ...
Muhammad Athif Mat Zin, Azmin Sham Rambely, Noratiqah Mohd Ariff, Muhammad Shahimi Ariffin   +3 more
doaj   +1 more source

Nonparametric Spline Truncated Regression with Knot Point Selection Method Generalized Cross Validation and Unbiased Risk

JTAM (Jurnal Teori dan Aplikasi Matematika), 2023
Nonparametric regression approaches are used when the shape of the regression curve between the response variable and the predictor variable is assumed to be unknown. Nonparametric excess regression has high flexibility.
Tutik Handayani, Sifriyani Sifriyani, Andrea Tri Rian Dani   +2 more
doaj   +1 more source

Exploring the Link Between Additive Heritability and Prediction Accuracy From a Ridge Regression Perspective

Frontiers in Genetics, 2020
Genome-Wide Association Studies (GWAS) explain only a small fraction of heritability for most complex human phenotypes. Genomic heritability estimates the variance explained by the SNPs on the whole genome using mixed models and accounts for the many ...
Arthur Frouin, Claire Dandine-Roulland, Morgane Pierre-Jean, Jean-François Deleuze, Jean-François Deleuze, Christophe Ambroise, Edith Le Floch   +6 more
doaj   +1 more source

Goodness of Fit Test of an Autocorrelated Time Series Cubic Smoothing Spline Model

Journal of Nigerian Society of Physical Sciences, 2021
We investigated the finite properties as well as the goodness of fit test for the cubic smoothing spline selection methods like the Generalized Maximum Likelihood (GML), Generalized Cross-Validation (GCV) and Mallow CP criterion (MCP) estimators for time-
Samuel Olorunfemi Adams, Davies Abiodun Obaromi, Alumbugu Auta Irinews   +2 more
doaj   +1 more source

Target Adaptive Differential Iterative Reconstruction (TADI): A Robust Algorithm for Real-Time Electrical Impedance Tomography

IEEE Access, 2021
Electrical impedance tomography (EIT) is a noninvasive functional diagnostic technique that has been successfully applied to human lung and brain. EIT reconstruction is an ill-conditioned problem: the regularization parameters establish a trade-off ...
Weirui Zhang, Tao Zhang, Xuechao Liu, Bin Yang, Meng Dai, Xuetao Shi, Xiuzhen Dong, Feng Fu, Canhua Xu   +8 more
doaj   +1 more source

Subsample Ridge Ensembles: Equivalences and Generalized Cross-Validation

CoRR, 2023
47 pages, 11 figures; this version fixes minor typos.
Jin-Hong Du, Pratik Patil, Arun Kumar Kuchibhotla   +2 more
openaire   +3 more sources

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
doaj   +1 more source

A Weighted Generalized Maximum Entropy Estimator with a Data-driven Weight

Entropy, 2009
The method of Generalized Maximum Entropy (GME), proposed in Golan, Judge and Miller (1996), is an information-theoretic approach that is robust to multicolinearity problem.
Ximing Wu
doaj   +1 more source

Asymptotic optimality of generalized C, cross-validation, and generalized cross-validation in regression with heteroskedastic errors [PDF]

Journal of Econometrics, 1991
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +2 more sources

Choice of Smoothing Parameter for Kernel Type Ridge Estimators in Semiparametric Regression Models

Revstat Statistical Journal, 2021
This paper concerns kernel-type ridge estimators of parameters in a semiparametric model. These estimators are a generalization of the well-known Speckman’s approach based on kernel smoothing method. The most important factor in achieving this smoothing
Ersin Yilmaz , Bahadir Yuzbasi , Dursun Aydin   +2 more
doaj   +1 more source