• mgcv

  • Referenced in 106 articles [sw07751]
  • Routines for GAMs and other generalized ridge regression with multiple smoothing parameter selection...
  • foba

  • Referenced in 30 articles [sw35840]
  • foba sparse learning algorithms for ridge regression, described in the paper ”Adaptive Forward-Backward Greedy...
  • RegEM

  • Referenced in 20 articles [sw04943]
  • replaces the conditional maximum likelihood estimation of regression parameters in the conventional EM algorithm ... squares (with fixed truncation parameter) and ridge regression with generalized cross-validation as regularized estimation ... regularized estimation of regression parameters (e.g., ridge regression and generalized cross-validation) can be exchanged...
  • penalized

  • Referenced in 28 articles [sw06071]
  • leave-one-out cross-validation for ridge regression. In model building and model evaluation, cross ... proportional hazards model with a ridge penalty term. Our approximation method is based...
  • Monomvn

  • Referenced in 14 articles [sw08173]
  • Through the use of parsimonious/shrinkage regressions (plsr, pcr, lasso, ridge, etc.), where standard regressions fail ... Horseshoe (from Carvalho, Polson, & Scott), and ridge regression with model selection via Reversible Jump...
  • blasso

  • Referenced in 13 articles [sw06769]
  • regression that provides a bridge between ridge regression and the lasso. The estimate that...
  • GCVPACK

  • Referenced in 13 articles [sw31699]
  • data analysis and data smoothing including ridge regression, thin plate smoothing splines, deconvolution, smoothing...
  • DiSCO

  • Referenced in 12 articles [sw28439]
  • discuss the results for distributed ridge regression, logistic regression and binary classification with a smoothed...
  • GeneMANIA

  • Referenced in 12 articles [sw30022]
  • fast heuristic algorithm, derived from ridge regression, to integrate multiple functional association networks and predict...
  • lmridge

  • Referenced in 5 articles [sw27784]
  • package lmridge: Linear Ridge Regression with Ridge Penalty and Ridge Statistics. Linear ridge regression coefficient...
  • WONDER

  • Referenced in 4 articles [sw35432]
  • WONDER: weighted one-shot distributed ridge regression in high dimensions. In many areas, practitioners need ... this area: How to do ridge regression in a distributed computing environment? Ridge regression ... methods that construct weighted combinations of ridge regression estimators computed on each machine. By analyzing ... Weighted ONe-shot DistributEd Ridge regression algorithm (WONDER). We test WONDER in simulation studies...
  • parcor

  • Referenced in 4 articles [sw14647]
  • methods: lasso, adaptive lasso, PLS, and Ridge Regression. In addition, the package provides model selection ... lasso, adaptive lasso and Ridge regression based on cross-validation...
  • rrBLUP

  • Referenced in 4 articles [sw14006]
  • rrBLUP: Ridge Regression and Other Kernels for Genomic Selection. Software for genomic prediction with ... estimate marker effects by ridge regression; alternatively, BLUPs can be calculated based on an additive...
  • ridge

  • Referenced in 3 articles [sw14859]
  • package ridge: Ridge Regression with automatic selection of the penalty parameter. This package contains functions ... fitting linear and logistic ridge regression models, including functions for fitting linear and logistic ridge...
  • lpridge

  • Referenced in 4 articles [sw07108]
  • package lpridge: Local Polynomial (Ridge) Regression. Local Polynomial Regression with Ridging...
  • R3P-Loc

  • Referenced in 2 articles [sw22444]
  • compact multi-label predictor using ridge regression and random projection for protein subcellular localization. Locating ... feature dimensions of an ensemble ridge regression (RR) classifier. Two new compact databases are created...
  • gwrr

  • Referenced in 3 articles [sw21074]
  • models with diagnostic tools. Fits geographically weighted regression (GWR) models and has tools to diagnose ... models. Also fits geographically weighted ridge regression (GWRR) and geographically weighted lasso (GWL) models...
  • plsdof

  • Referenced in 3 articles [sw12201]
  • mean and covariance of the PLS regression coefficients are available. They allow the construction ... procedures. Further, cross-validation procedures for Ridge Regression and Principal Components Regression are available...
  • BhGLM

  • Referenced in 3 articles [sw10342]
  • special cases, e.g., classical GLMs, ridge regression, Bayesian lasso, and various adaptive lasso. These methods...
  • Expectreg

  • Referenced in 15 articles [sw14660]
  • quantile regression of models with nonlinear effects e.g. spatial, random, ridge using least asymmetric weighed...