
gss
 Referenced in 282 articles
[sw06099]
 less. Smoothing spline ANOVA models are a versatile family of smoothing methods derived through roughness ... penalty smoothing under a unified framework. Methods are developed for (i) regression with Gaussian...

SemiPar
 Referenced in 705 articles
[sw07116]
 semiparametric regression is based on penalized regression splines and mixed models. Every model in this ... scientists with only a moderate background in regression, though familiarity with matrix and linear algebra ... interest even to experts on smoothing, and they are a third possible audience. This book...

cobs
 Referenced in 9 articles
[sw21863]
 Splines (Sparse Matrix Based). Qualitatively Constrained (Regression) Smoothing Splines via Linear Programming and Sparse Matrices...

GCVPACK
 Referenced in 13 articles
[sw31699]
 data smoothing including ridge regression, thin plate smoothing splines, deconvolution, smoothing of generalized linear models...

bigsplines
 Referenced in 2 articles
[sw16387]
 package bigsplines. Fits smoothing spline regression models using scalable algorithms designed for large samples...

MortalitySmooth
 Referenced in 12 articles
[sw10483]
 interested in using a practical tool for smoothing mortality data over ages and/or years ... splines and generalized linear array models are employed as a suitable regression methodology. ExtraPoisson...

SPLINTER
 Referenced in 3 articles
[sw15719]
 function approximation, regression, data smoothing, data reduction, and much more. Spline approximations are represented...

Proc_R_med
 Referenced in 1 article
[sw36092]
 GLMs, but also multiple additive regression trees and smoothing splines...

ibr
 Referenced in 7 articles
[sw11227]
 underlying smoothness of the true regression function. Our estimator is easily computed by successive application ... selecting an optimal smoothing parameter), such as thinplate spline or kernel smoothers. The resulting ... knowledge, no other adaptive fully nonparametric regression estimator is available without constrained assumption such...

cpr
 Referenced in 1 article
[sw20286]
 reduction’ (CNR). BSplines are commonly used in regression models to smooth data and approximate ... with respect to the quality of the regression models. The focus...

cosso
 Referenced in 1 article
[sw23471]
 package cosso: Fit Regularized Nonparametric Regression Models Using COSSO Penalty. COSSO is a new regularization ... context of smoothing spline ANOVA models. Implemented models include mean regression, quantile regression, logistic regression...

CDGAM
 Referenced in 1 article
[sw26138]
 regression basis may include components from the family of smoothing splines...

PROC GAM
 Referenced in 1 article
[sw12075]
 local regression and the TPSPLINE procedure for thinplate smoothing splines. The generalized additive models ... normally distributed. See the section Nonparametric Regression for more details on the form of generalized...

CIP
 Referenced in 2 articles
[sw12675]
 smoothing (with cubic splines), clustering (kmedoids, ART2a) and machine learning (multiple linear/polynomial regression...

SmoothHazard
 Referenced in 4 articles
[sw14710]
 censored data are also allowed. Proportional intensities regression models allow for covariates on each ... with Msplines approximation of baseline intensities in order to obtain smooth estimates. Estimation...

BARS
 Referenced in 4 articles
[sw10487]
 jump MCMC engine to perform splinebased generalized nonparametric regression. It has been shown ... producing visuallyappealing fits that are smooth (filtering out highfrequency noise) while adapting ... needed subroutines for fitting Poisson regression, manipulating Bsplines (using code created by Bates...

quantregGrowth
 Referenced in 1 article
[sw32615]
 regression quantiles as a function of linear covariates and multiple smooth terms via Bsplines...

SmoothHR
 Referenced in 3 articles
[sw11464]
 continuous predictors. The Cox proportional hazards regression model has become the traditional choice for modeling ... model, several smoothing methods may be applied, and approaches based on splines are the most...

BFDA
 Referenced in 2 articles
[sw14769]
 that implements a Bayesian hierarchical model for smoothing functional data and estimating meancovariance functions ... Bayesian inference process with cubic Bspline basis functions is integrated in this toolbox, which ... scale functional data. Examples of functional data regression with one functional independent variable, scalar ... advantages of BFDA include: (1) Simultaneously smooths functional data and estimates the meancovariance functions...

NestedCompRisks
 Referenced in 1 article
[sw36437]
 state structured additive regression (STAR) models combined with penalized splines (Psplines) are proposed ... smooth estimates of baseline transition intensities and the inclusion of timevarying and smooth covariate ... timedependent predictive accuracy of a given regression model, which is typically assessed using receiver...