• gss

  • Referenced in 268 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 677 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 8 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 11 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. Extra-Poisson...
  • SPLINTER

  • Referenced in 3 articles [sw15719]
  • function approximation, regression, data smoothing, data reduction, and much more. Spline approximations are represented...
  • 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 thin-plate 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). B-Splines 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 thin-plate 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 (k-medoids, ART-2a) 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 M-splines approximation of baseline intensities in order to obtain smooth estimates. Estimation...
  • BARS

  • Referenced in 4 articles [sw10487]
  • jump MCMC engine to perform spline-based generalized nonparametric regression. It has been shown ... producing visually-appealing fits that are smooth (filtering out high-frequency noise) while adapting ... needed subroutines for fitting Poisson regression, manipulating B-splines (using code created by Bates...
  • quantregGrowth

  • Referenced in 1 article [sw32615]
  • regression quantiles as a function of linear covariates and multiple smooth terms via B-splines...
  • BFDA

  • Referenced in 2 articles [sw14769]
  • that implements a Bayesian hierarchical model for smoothing functional data and estimating mean-covariance functions ... Bayesian inference process with cubic B-spline 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 mean-covariance functions...
  • SmoothHR

  • Referenced in 2 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...
  • L2WPMA

  • Referenced in 8 articles [sw04326]
  • problem (monotonic fit or isotonic regression) for each set. So it calculates efficiently a global ... calculation a spline representation of the solution and the corresponding Lagrange multipliers are provided ... providing a preliminary or complementary smoothing phase to further analyses of the data...
  • npbr

  • Referenced in 1 article [sw15636]
  • package npbr: Nonparametric Boundary Regression. A variety of functions for the best known and most ... selected methods are concerned with empirical, smoothed, unrestricted as well as constrained fits under both ... data envelopment techniques based on piecewise polynomials, splines, local linear fitting, extreme values and kernel...