• mgcv

  • Referenced in 73 articles [sw07751]
  • Routines for GAMs and other generalized ridge regression with multiple smoothing parameter selection...
  • foba

  • Referenced in 25 articles [sw35840]
  • foba sparse learning algorithms for ridge regression, described in the paper ”Adaptive Forward-Backward Greedy...
  • penalized

  • Referenced in 24 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...
  • RegEM

  • Referenced in 16 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...
  • blasso

  • Referenced in 12 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...
  • Monomvn

  • Referenced in 10 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...
  • GeneMANIA

  • Referenced in 9 articles [sw30022]
  • fast heuristic algorithm, derived from ridge regression, to integrate multiple functional association networks and predict...
  • DiSCO

  • Referenced in 8 articles [sw28439]
  • discuss the results for distributed ridge regression, logistic regression and binary classification with a smoothed...
  • lmridge

  • Referenced in 4 articles [sw27784]
  • package lmridge: Linear Ridge Regression with Ridge Penalty and Ridge Statistics. Linear ridge regression coefficient...
  • 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...
  • rrBLUP

  • Referenced in 3 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...
  • parcor

  • Referenced in 2 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...
  • 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...
  • 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...
  • WONDER

  • Referenced in 1 article [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...
  • lrmest

  • Referenced in 1 article [sw27785]
  • Ordinary Least Square Estimator (OGOLSE), Ordinary Ridge Regression Estimator (ORRE), Ordinary Generalized Ridge Regression Estimator ... Mixed Regression Estimator (OMRE), Ordinary Generalized Mixed Regression Estimator (OGMRE), Liu Estimator (LE), Ordinary Generalized ... Type-1,2,3 OGALTE), Almost Unbiased Ridge Estimator (AURE), Ordinary Generalized Almost Unbiased Ridge ... Stochastic Restricted Ridge Estimator (OGSRRE), Restricted Ridge Regression Estimator (RRRE) and Ordinary Generalized Restricted Ridge...
  • Expectreg

  • Referenced in 13 articles [sw14660]
  • quantile regression of models with nonlinear effects e.g. spatial, random, ridge using least asymmetric weighed...