
SemiPar
 Referenced in 588 articles
[sw07116]
 approach to semiparametric regression is based on penalized regression splines and mixed models. Every model ... desire to begin using more flexible semiparametric models. There is enough new material...

timereg
 Referenced in 59 articles
[sw08068]
 Plus more recent developments. Additive survival model, semiparametric proportional odds model, fast cumulative residuals, excess...

XploRe
 Referenced in 54 articles
[sw01128]
 focus is put on non and semiparametric modelling and the statistics of financial markets...

DPpackage
 Referenced in 47 articles
[sw10495]
 robustness against misspecification of the probability model. In the Bayesian context, this is accomplished ... implementation of some Bayesian nonparametric and semiparametric models in R, DPpackage. Currently, DPpackage includes models...

huge
 Referenced in 27 articles
[sw08466]
 functions for fitting high dimensional semiparametric Gaussian copula models; (3) more functions like datadependent...

tgp
 Referenced in 27 articles
[sw07921]
 Bayesian treed Gaussian process models. Bayesian nonstationary, semiparametric nonlinear regression and design by treed Gaussian ... with jumps to the limiting linear model (LLM). Special cases also implemented include Bayesian linear...

SemiParBIVProbit
 Referenced in 13 articles
[sw08169]
 Modelling. Routine for fitting bivariate probit models with semiparametric predictors (including linear and nonlinear effects ... equations, endogeneity or sample selection. Bivariate copula models are also supported...

PSPMCM
 Referenced in 6 articles
[sw27707]
 macro for parametric and semiparametric mixture cure models. Cure models have been developed to analyze ... possibility of cure. Mixture cure models assume that the studied population is a mixture ... macro to estimate parametric and semiparametric mixture cure models with covariates. The cure fraction ... various binary regression models. Parametric and semiparametric models can be used to model the survival...

np
 Referenced in 66 articles
[sw10543]
 package implements a variety of nonparametric and semiparametric kernelbased estimators that are popular among ... nonparametric tests of significance and consistent model specification tests for parametric mean regression models...

depend.truncation
 Referenced in 4 articles
[sw11100]
 depend.truncation: Statistical inference for parametric and semiparametric models based on dependently truncated data. The package ... performs parametric and semiparametric inferences for models based on dependently truncated data. Semiparametric approaches...

Smcure
 Referenced in 5 articles
[sw16862]
 smcure: Fit Semiparametric Mixture Cure Models. An Rpackage for Estimating Semiparametric...

spBayesSurv
 Referenced in 5 articles
[sw16371]
 failure time frailty models, and standard semiparametric frailty models within the context of proportional hazards...

HMMmix
 Referenced in 4 articles
[sw13500]
 emission distributions. In unsupervised classification, Hidden Markov Models (HMM) are used to account ... parametric family. In this paper, a semiparametric model where the emission distributions are a mixture...

Proc Traj
 Referenced in 11 articles
[sw11097]
 fitting a mixture model. The TRAJ procedure fits semiparametric (discrete) mixtures of censored normal, Poisson ... information criterion to address the problem of model selection, including the estimation of the number...

sampleSelection
 Referenced in 10 articles
[sw08258]
 implementation of Heckmantype sample selection models in R. We discuss the sample selection problem ... semiparametric estimation methods in its toolbox, Heckman models are an integral part of the modern...

frailtySurv
 Referenced in 3 articles
[sw19047]
 General Semiparametric Shared Frailty Model Estimation and Simulation with frailtySurv. The R package frailtySurv...

ICsurv
 Referenced in 2 articles
[sw23156]
 model. More methods under other semiparametric regression models will be included in later versions...

psbcGroup
 Referenced in 2 articles
[sw24007]
 package psbcGroup: Penalized Parametric and Semiparametric Bayesian Survival Models with Shrinkage and Grouping Priors. Algorithms ... fitting penalized parametric and semiparametric Bayesian survival models with shrinkage and grouping priors...

bspmma
 Referenced in 1 article
[sw19269]
 package bspmma: bspmma: Bayesian Semiparametric Models for MetaAnalysis. Some functions for nonparametric and semiparametric...

pgam
 Referenced in 1 article
[sw25118]
 Poisson count data, PoissonGamma model, towards a semiparametric specification. Just like the generalized additive ... used for covariate smoothing. The semiparametric models are fitted by an iterative process that combines...