Lasso Penalized Quantile RegressionR. Koenker
In the regression set- ting, let y i be the response for case i, x ij be the value of predictor j for case i, and β j be the regression coefficient corresponding to predictor j. The in- tercept µ is ignored in the lasso penalty, whose strength is determined by the Received ...
LASSO是纯算法的解法，他是LAR（least angle regression）的升级版本，解法也一样，就是一个iteration的...
Generalized linear mixed models (GLMMs), typically used for analyzing correlated data, can also be used for smoothing by considering the knot coefficients from a regression spline as random effects. The resulting models are called semiparametric mixed models (SPMMs). Allowing the random knot coefficie...
LASSO是纯算法的解法，他是LAR（least angle regression）的升级版本，解法也一样，就是一个iteration的...
Regularization Paths for Huber Loss Regression and Quantile Regression Penalized by Lasso or Elastic-Net To install: the released version from CRAN:install.packages("hqreg") the latest version (requiredevtools):install_github("CY-dev/hqreg") ...
glmnet, for computing penalized regression library(tidyverse) library(caret) library(glmnet) ... Citation:http://www.sthda.com/english/articles/37-model-selection-essentials-in-r/153-penalized-regression-essentials-ridge-lasso-elastic-net/
Clusterwise linear regressionpenalized likelihoodregularized MLcovariate selectionIn clusterwise regression analysis, the goal is to predict a response variable based on a set of explanatory variables, each with cluster-specific effects. In many real-life problems, the number of candidate predictors is ...
Clusterwise Linear RegressionPenalized LikelihoodRegularized MLCovariate SelectionIn clusterwise regression analysis, the goal is to predict a response variable based on a set of explanatory variables, each with cluster-specific effects. NowaDi Mari, Roberto...
Tong Tong Wu, Yi Fang Chen, Trevor Hastie, Eric Sobel, and Kenneth Lange. Genome-wide association analysis by lasso penalized logistic regression. Bioinformatics (Oxford, England), 25(6):714-21, March 2009.Wu, T. T., Chen, Y. F., Hastie, T., Sobel, E. & Lange, K. (2009), `...