• SemiPar

  • Referenced in 686 articles [sw07116]
  • They refer to this combination as semiparametric regression. The approach to semiparametric regression is based ... scientists with only a moderate background in regression, though familiarity with matrix and linear algebra ... desire to begin using more flexible semiparametric models. There is enough new material...
  • tgp

  • Referenced in 35 articles [sw07921]
  • treed Gaussian process models. Bayesian nonstationary, semiparametric nonlinear regression and design by treed Gaussian processes...
  • timereg

  • Referenced in 74 articles [sw08068]
  • Regression Models for Survival Data’, Springer Verlag. Plus more recent developments. Additive survival model, semiparametric ... risk models and more. Flexible competing risks regression including GOF-tests. Two-stage frailty modelling...
  • ICsurv

  • Referenced in 4 articles [sw23156]
  • package ICsurv: A package for semiparametric regression analysis of interval-censored data. Currently using ... model. More methods under other semiparametric regression models will be included in later versions...
  • np

  • Referenced in 91 articles [sw10543]
  • package implements a variety of nonparametric and semiparametric kernel-based estimators that are popular among ... consistent model specification tests for parametric mean regression models and parametric quantile regression models, among...
  • DPpackage

  • Referenced in 62 articles [sw10495]
  • probability distributions or the space of all regression functions. Unfortunately, posterior distributions ranging over function ... implementation of some Bayesian nonparametric and semiparametric models in R, DPpackage. Currently, DPpackage includes models ... characteristic curve analysis, interval-censored data, binary regression data, item response data, longitudinal and clustered...
  • AdaptFit

  • Referenced in 3 articles [sw10486]
  • SemiPar package fits semiparametric regression models with spatially adaptive penalized splines...
  • PSPMCM

  • Referenced in 8 articles [sw27707]
  • macro to estimate parametric and semiparametric mixture cure models with covariates. The cure fraction ... modelled by various binary regression models. Parametric and semiparametric models can be used to model...
  • McSpatial

  • Referenced in 2 articles [sw16522]
  • package McSpatial. Locally weighted regression, semiparametric and conditionally parametric regression, fourier and cubic spline functions...
  • PCDSpline

  • Referenced in 1 article [sw31379]
  • package PCDSpline: Semiparametric regression analysis of panel count data using monotone splines. Semiparametric regression analysis...
  • semibart

  • Referenced in 1 article [sw31324]
  • semiparametric modeling approach using Bayesian additive regression trees with an application to evaluate heterogeneous treatment ... effects. Bayesian Additive Regression Trees (BART) is a flexible machine learning algorithm capable of capturing ... covariates. We extend BART to a semiparametric regression framework in which the conditional expectation ... form. The result is a Bayesian semiparametric linear regression model where the posterior distribution...
  • regpro

  • Referenced in 1 article [sw19267]
  • nonparametric regression (kernel, local linear), (2) semiparametric regression (single index, additive models), and (3) quantile...
  • ICBayes

  • Referenced in 1 article [sw26412]
  • Data. Contains functions to fit Bayesian semiparametric regression survival models (proportional hazards model, proportional odds...
  • FoSIntro

  • Referenced in 2 articles [sw36459]
  • package to: An introduction to semiparametric function-on-scalar regression. Function-on-scalar regression models ... introduction for a flexible semiparametric approach for function-on-scalar regression, using spatially referenced time...
  • spsurv

  • Referenced in 1 article [sw32477]
  • reliable routines to ease semiparametric survival regression modeling based on Bernstein polynomials. ’spsurv’ includes proportional...
  • haldensify

  • Referenced in 1 article [sw35416]
  • based on a pooled hazard regression formulation and semiparametric estimation via conditional hazards modeling ... highly adaptive lasso, a nonparametric regression function for efficient estimation with fast convergence under mild...
  • semsfa

  • Referenced in 1 article [sw33881]
  • procedure: in the first step semiparametric or nonparametric regression techniques are used to relax parametric...
  • eigenmodel

  • Referenced in 1 article [sw26199]
  • package eigenmodel: Semiparametric Factor and Regression Models for Symmetric Relational Data. Estimation of the parameters...
  • SISIR

  • Referenced in 1 article [sw31333]
  • Sliced Inverse Regression. An interval fusion procedure for functional data in the semiparametric framework...
  • NestedCompRisks

  • Referenced in 1 article [sw36437]
  • methodology to evaluate the predictive accuracy of semiparametric multi-state models in the presence ... complexity of such programmes. Multi-state regression models taking competing risks into account...