• mgcv

  • Referenced in 82 articles [sw07751]
  • with GCV/AIC/REML smoothness estimation. Routines for GAMs and other generalized ridge regression with multiple smoothing...
  • RegEM

  • Referenced in 17 articles [sw04943]
  • method replaces the conditional maximum likelihood estimation of regression parameters in the conventional EM algorithm ... truncation parameter) and ridge regression with generalized cross-validation as regularized estimation methods. The implementation ... that perform he regularized estimation of regression parameters (e.g., ridge regression and generalized cross-validation...
  • blasso

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

  • Referenced in 1 article [sw27785]
  • Ordinary Least Square Estimator (OGOLSE), Ordinary Ridge Regression Estimator (ORRE), Ordinary Generalized Ridge Regression Estimator ... Regression Estimator (OGMRE), Liu Estimator (LE), Ordinary Generalized Liu Estimator (OGLE), Restricted Liu Estimator ... Estimator (OGRLE), Stochastic Restricted Liu Estimator (SRLE), Ordinary Generalized Stochastic Restricted Liu Estimator (OGSRLE), Type ... Stochastic Restricted Ridge Estimator (OGSRRE), Restricted Ridge Regression Estimator (RRRE) and Ordinary Generalized Restricted Ridge...
  • lmridge

  • Referenced in 4 articles [sw27784]
  • Penalty and Ridge Statistics. Linear ridge regression coefficient’s estimation and testing with different ridge...
  • ragt2ridges

  • Referenced in 2 articles [sw19497]
  • package ragt2ridges: Ridge Estimation of Vector Auto-Regressive (VAR) Processes. Ridge maximum likelihood estimation...
  • rrBLUP

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

  • Referenced in 1 article [sw35432]
  • methods that construct weighted combinations of ridge regression estimators computed on each machine. By analyzing ... phenomena. Infinite-worker limit: The distributed estimator works well for very large numbers of machines ... local estimators sum to more than unity, due to the downward bias of ridge. Thus ... Weighted ONe-shot DistributEd Ridge regression algorithm (WONDER). We test WONDER in simulation studies...
  • Monomvn

  • Referenced in 10 articles [sw08173]
  • Student-t data with monotone missingness. Estimation of multivariate normal and student-t data ... Through the use of parsimonious/shrinkage regressions (plsr, pcr, lasso, ridge, etc.), where standard regressions fail...
  • ltsbase

  • Referenced in 2 articles [sw27788]
  • estimate Ridge and Liu estimators based on LTS method in multiple linear regression analysis...
  • penalized

  • Referenced in 24 articles [sw06071]
  • leave-one-out cross-validation for ridge regression. In model building and model evaluation, cross ... ridge penalty term. Our approximation method is based on a Taylor expansion around the estimate...
  • RKHSMetaMod

  • Referenced in 1 article [sw28872]
  • estimate the Hoeffding decomposition of an unknown function by solving RKHS Ridge Group Sparse optimization ... Gaussian regression model, RKHSMetaMod estimates a meta model by solving the Ridge Group Sparse Optimization ... terms estimate the terms in the Hoeffding decomposition of the unkwown regression function. This package...
  • parcor

  • Referenced in 2 articles [sw14647]
  • package estimates the matrix of partial correlations based on different regularized regression methods: lasso, adaptive ... lasso, PLS, and Ridge Regression. In addition, the package provides model selection for lasso, adaptive...
  • RXshrink

  • Referenced in 2 articles [sw27789]
  • Maximum Likelihood Shrinkage via Generalized Ridge or Least Angle Regression. Identify and display TRACEs ... optimal reduction in MSE Risk in estimates of regression (beta) coefficients. Alternative estimates are also...
  • HDCI

  • Referenced in 2 articles [sw32617]
  • estimate coefficients and use bootstrap method to obtain confidence intervals. Choices for regression models ... Lasso, Lasso+OLS, Lasso partial ridge, Lasso+OLS partial ridge...
  • plsdof

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

  • Referenced in 1 article [sw27786]
  • univariate ridge trace plot used in ridge regression and related methods. These graphical methods show ... plotting the covariance ellipsoids of the estimated coefficients, rather than just the estimates themselves...
  • MultiwayRegression

  • Referenced in 1 article [sw18394]
  • Tensor-on-tensor regression. We propose a framework for the linear prediction of a multi ... penalized least-squares estimation, which allows for a ridge (L_2) penalty on the coefficients...
  • RuleFit

  • Referenced in 1 article [sw20934]
  • procedures from the lasso to ridge regression, thereby allowing the user to decrease the sparsity ... accurate models and more honest (less optimistic) estimates of future prediction error. This is especially...
  • stR

  • Referenced in 0 articles [sw16590]
  • some ways, STR is similar to Ridge Regression and Robust STR can be related ... methods provide confidence intervals for the estimated components. The methods can be used for forecasting...