• nlmdl

  • Referenced in 116 articles [sw27811]
  • univariate nonlinear regression model and generalized least squares estimates for a multivariate nonlinear regression model ... implicit form, it computes three-stage least-squares estimates, TSLS option, and for nonlinear dynamic...
  • pls

  • Referenced in 31 articles [sw04365]
  • Partial Least Squares and Principal Component regression , Multivariate regression methods Partial Least Squares Regression (PLSR ... Principal Component Regression (PCR) and Canonical Powered Partial Least Squares (CPPLS...
  • LIBRA

  • Referenced in 28 articles [sw10553]
  • ROBPCA), Principal Component Regression (RPCR), Partial Least Squares Regression (RSIMPLS), classification (RDA, RSIMCA), clustering, outlier...
  • mboost

  • Referenced in 62 articles [sw07331]
  • functions utilizing component-wise (penalised) least squares estimates or regression trees as base-learners...
  • gbm

  • Referenced in 50 articles [sw07994]
  • gradient boosting machine. Includes regression methods for least squares, absolute loss, t-distribution loss, quantile...
  • bmrm

  • Referenced in 22 articles [sw11016]
  • regression, quantile regression, epsilon insensitive regression, least mean square, logistic regression, least absolute deviation regression...
  • rms

  • Referenced in 90 articles [sw04532]
  • least squares for serially or spatially correlated observations, generalized linear models, and quantile regression...
  • lars

  • Referenced in 41 articles [sw08165]
  • package lars: Least Angle Regression, Lasso and Forward Stagewise. Efficient procedures for fitting an entire ... cost of a single least squares fit. Least angle regression and infinitesimal forward stagewise regression...
  • Bolasso

  • Referenced in 28 articles [sw31649]
  • bootstrap. We consider the least-square linear regression problem with regularization by the l1-norm...
  • Statistics Toolbox

  • Referenced in 18 articles [sw10157]
  • analyzing, and modeling data. You can use regression or classification for predictive modeling, generate random ... regularization and shrinkage, or use partial least squares regression. The toolbox provides supervised and unsupervised...
  • grf

  • Referenced in 15 articles [sw27871]
  • currently provides methods for non-parametric least-squares regression, quantile regression, and treatment effect estimation...
  • spls

  • Referenced in 10 articles [sw09507]
  • package spls: Sparse Partial Least Squares (SPLS) Regression and Classification. This package provides ... functions for fitting a Sparse Partial Least Squares Regression and Classification...
  • gglasso

  • Referenced in 17 articles [sw14361]
  • group-lasso penalized least squares, logistic regression, Huberized SVM and squared...
  • ADE-4

  • Referenced in 8 articles [sw14077]
  • polynomial regression, multiple and PLS (partial least squares) regression and orthogonal regression (principal component regression...
  • Systemfit

  • Referenced in 13 articles [sw08894]
  • Least Squares (OLS), Weighted Least Squares (WLS), Seemingly Unrelated Regressions (SUR), Two-Stage Least Squares...
  • xtscc

  • Referenced in 7 articles [sw37339]
  • Robust standard errors for panel regressions with cross-sectional dependence. I present a new Stata ... pooled or- dinary least-squares/weighted least-squares regression and fixed-effects (within) regression models...
  • plsRglm

  • Referenced in 4 articles [sw12196]
  • plsRglm: Partial Least Squares Regression for Generalized Linear Models. Provides (weighted) Partial least squares Regression...
  • PERMON

  • Referenced in 5 articles [sw16719]
  • also arise in other disciplines like least-squares regression, data fitting, data mining, support vector...
  • RegEM

  • Referenced in 17 articles [sw04943]
  • replaces the conditional maximum likelihood estimation of regression parameters in the conventional EM algorithm ... provide truncated total least squares (with fixed truncation parameter) and ridge regression with generalized cross...
  • LSS

  • Referenced in 4 articles [sw20471]
  • right censored data based on least-squares principle. Due to lack of proper inference procedure ... software, the ordinary linear regression model is seldom used in practice for the analysis ... Ying, On least-squares regression with censored data, Biometrika ... failure time model based on the least-squares principle. The program is user-friendly...