
SemiPar
 Referenced in 761 articles
[sw07116]
 based on penalized regression splines and mixed models. Every model in this book ... special case of the linear mixed model or its generalized counterpart. This book is very ... from their collaborative research have driven the selection of material and emphases and are used...

gss
 Referenced in 317 articles
[sw06099]
 general penalized likelihood method and the construction of multivariate models with builtin ANOVA decompositions ... Extensive discussions are devoted to model construction, smoothing parameter selection, computation, and asymptotic convergence. Most...

quantreg
 Referenced in 162 articles
[sw04356]
 parametric and nonparametric (total variation penalized) models for conditional quantiles of a univariate response ... methods for handling censored survival data. Portfolio selection methods based on expected shortfall risk...

CAPUSHE
 Referenced in 62 articles
[sw13365]
 Slope heuristics: overview and implementation. Model selection is a general paradigm which includes many statistical ... minimization of a penalized criterion. L. Birgé and P. Massart [Probab. Theory Relat. Fields...

capushe
 Referenced in 5 articles
[sw28004]
 Using Slope HEuristics. Calibration of penalized criteria for model selection. The calibration methods available...

glmmLasso
 Referenced in 8 articles
[sw14724]
 glmmLasso: Variable Selection for Generalized Linear Mixed Models by L1penalized Estimation. R package...

ppls
 Referenced in 5 articles
[sw24174]
 Partial Least Squares and Penalization Techniques. Model parameters are selected via crossvalidation, and confidence...

OSCAR
 Referenced in 58 articles
[sw03026]
 similar behavior. The technique is based on penalized least squares with a geometrically intuitive penalty ... variable selection techniques in terms of both prediction error and model complexity, while yielding...

qrcmNP
 Referenced in 2 articles
[sw35602]
 penalized approach to covariate selection through quantile regression coefficient models. The coefficients of a quantile ... time. Another possibility is to model the coefficient functions parametrically, an approach that is referred ... penalized method that can address the selection of covariates in this particular modelling ... framework. Unlike standard penalized quantile regression estimators, in which model selection is quantilespecific...

QICD
 Referenced in 20 articles
[sw19679]
 Coefficients for NonConvex Penalized Quantile Regression Model by using QICD Algorithm. Extremely fast algorithm ... Coordinate Descent Algorithm for Highdimensional Nonconvex Penalized Quantile Regression. This algorithm combines the coordinate ... median, which ensures fast computation. Tuning parameter selection is based on two different method ... cross validation and BIC for quantile regression model. Details are described in Peng...

MixMoGenD
 Referenced in 6 articles
[sw08624]
 model selection problem. The competing models are compared using penalized maximum likelihood criteria. Under weak ... associated algorithm named mixture model for genotype data (MixMoGenD) has been implemented using C++ programming ... avoid an exhaustive search of the optimum model, we propose a modified BackwardStepwise algorithm ... enables a better search of the optimum model among all possible cardinalities...

crrp
 Referenced in 2 articles
[sw28755]
 package crrp: Penalized Variable Selection in Competing Risks Regression. In competing risks regression, the proportional ... subdistribution hazards(PSH) model is popular for its direct assessment of covariate effects ... This package allows for penalized variable selection for the PSH model. Penalties include LASSO, SCAD...

Plus
 Referenced in 3 articles
[sw08189]
 Penalized Linear Unbiased Selection. Efficient procedures for fitting an entire regression sequences with different model...

scam
 Referenced in 7 articles
[sw15787]
 Penalized likelihood maximization based on NewtonRaphson method is used to fit a model with ... multiple smoothing parameter selection by GCV or UBRE/AIC...

cntclust
 Referenced in 7 articles
[sw40587]
 mild and gross outliers. We propose a modelbased clustering procedure where each component ... trimmed. We propose a penalized likelihood approach for estimation and selection of the proportions ... without trimming, and over trimmed normal mixture models ( exttt{tclust}). We conclude with an original...

HurdleNormal
 Referenced in 1 article
[sw30708]
 estimate graphical models using grouplasso penalized neighborhood selection...

piMASS
 Referenced in 20 articles
[sw17249]
 naturally be cast as a variable selection regression problem, with the SNPs as the covariates ... model, which we argue is a strength of BVSR compared with alternatives such as penalized...

cvplogistic
 Referenced in 5 articles
[sw29394]
 solution surface for concave penalized logistic regression model. The SCAD and MCP (default ... Lassoconcave hybrid penalty for fast variable selection. The hybrid penalty applies the concave penalty...

lassopack
 Referenced in 1 article
[sw37548]
 lassopack: Model selection and prediction with regularized regression in Stata. In this article, we introduce ... offer three approaches for selecting the penalization (“tuning”) parameters: information criteria (implemented in lasso2...

rope
 Referenced in 1 article
[sw21810]
 Selected Variables. Selects one model with variable selection FDR controlled at a specified level ... variable selection counts over many bootstraps for several levels of penalization, is modeled as coming...