Results 31 to 40 of about 170,593 (200)
P-spline anova-type interaction models for spatio-temporal smoothing [PDF]
, 2009 In recent years, spatial and spatio-temporal modelling have become an important area of research in many fields (epidemiology, environmental studies, disease mapping, ...).
Lee, Dae-Jin +1 more
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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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Fuzzy clustering of time series gene expression data with cubic-spline [PDF]
, 2013 Data clustering techniques have been applied to ex- tract information from gene expression data for two decades. A large volume of novel clustering algorithms have been developed and achieved great success.
Ali, Akhtar, Wang, Yu, Angelova, Maia
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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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Efficient estimation of smoothing spline with exact shape constraints
Statistical Theory and Related Fields, 2021 Smoothing spline is a popular method in non-parametric function estimation. For the analysis of data from real applications, specific shapes on the estimated function are often required to ensure the estimated function undeviating from the domain ...
Vincent Chan +4 more
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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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Diagnostics for Smoothing Splines
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1985 SUMMARY Diagnostic measures appropriate for use with smoothing splines are derived and their properties are investigated. The proposed measures focus on detection of observations which substantially influence the fit and provide additional information over that obtained from examination of residuals alone. A numerical example illustrates
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On algorithms for generalised smoothing splines [PDF]
The Journal of the Australian Mathematical Society. Series B. Applied Mathematics, 1988 AbstractRecently, considerable interest has been shown in the connection between smoothing splines and a particular class of stochastic processes. Here the connection with an equivalent class of least squares problems is used to develop algorithms, and properties of the solution are examined.
Osborne, M. R., Prvan, Tania
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