Results 21 to 30 of about 16,443 (262)
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 +3 more
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Applied Sciences, 2021 Meta-model sre generally applied to approximate multi-objective optimization, reliability analysis, reliability based design optimization, etc., not only in order to improve the efficiencies of numerical calculation and convergence, but also to ...
Chang-Yong Song
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A comparison of spatial analysis methods for the construction of topographic maps of retinal cell density. [PDF]
PLoS ONE, 2014 Topographic maps that illustrate variations in the density of different neuronal sub-types across the retina are valuable tools for understanding the adaptive significance of retinal specialisations in different species of vertebrates. To date, such maps
Eduardo Garza-Gisholt +3 more
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Use of nonparametric regression methods for developing a local stem form model
Journal of Forest Science, 2014 A local mean stem curve of spruce was represented using regression splines. Abilities of smoothing spline and P-spline to model the mean stem curve were evaluated using data of 85 carefully measured stems of Norway spruce. For both techniques the optimal
K. Kuželka, R. Marušák
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A-Spline Regression for Fitting a Nonparametric Regression Function with Censored Data
Stats, 2020 This paper aims to solve the problem of fitting a nonparametric regression function with right-censored data. In general, issues of censorship in the response variable are solved by synthetic data transformation based on the Kaplan–Meier estimator in the
Ersin Yılmaz +2 more
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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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Equivalent Kernels for Smoothing Splines [PDF]
Journal of Integral Equations and Applications, 2006 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Eggermont, P.P.B., LaRiccia, V.N.
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JTAM (Jurnal Teori dan Aplikasi Matematika)Path analysis is used to determine the effect of exogenous variables on endogenous variables. One of the assumptions in path analysis is the linearity assumption. The linearity assumption can be tested using Ramsey RESET.
Muhammad Rafi Hasan Nurdin +3 more
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Smoothing Spline ANOVA Models: R Package gss
Journal of Statistical Software, 2014 This document provides a brief introduction to the R package gss for nonparametric statistical modeling in a variety of problem settings including regression, density estimation, and hazard estimation.
Chong Gu
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Precise Tensor Product Smoothing via Spectral Splines
StatsTensor product smoothers are frequently used to include interaction effects in multiple nonparametric regression models. Current implementations of tensor product smoothers either require using approximate penalties, such as those typically used in ...
Nathaniel E. Helwig
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