• WFMM

  • Referenced in 6 articles [sw36436]
  • result of the nonlinear shrinkage prior imposed on the fixed effects wavelet coefficients...
  • BayesReg

  • Referenced in 3 articles [sw31836]
  • Bayesian Regression Models with Global-Local Shrinkage Priors. Fits linear or logistic regression model using ... Bayesian global-local shrinkage prior hierarchies as described in Polson and Scott...
  • horserule

  • Referenced in 4 articles [sw27913]
  • horseshoe prior, which is well known to give aggressive shrinkage of noise predictors while leaving ... horseshoe prior has an additional hierarchical layer that applies more shrinkage a priori to rules ... observations. The aggressive noise shrinkage of our prior also makes it possible to complement...
  • psbcGroup

  • Referenced in 3 articles [sw24007]
  • Semiparametric Bayesian Survival Models with Shrinkage and Grouping Priors. Algorithms for fitting penalized parametric ... semiparametric Bayesian survival models with shrinkage and grouping priors...
  • MBSP

  • Referenced in 1 article [sw25620]
  • package MBSP: Multivariate Bayesian Model with Shrinkage Priors. Implements a sparse Bayesian multivariate linear regression ... model using shrinkage priors from the three parameter beta normal family. The method is described...
  • bayesreg

  • Referenced in 1 article [sw31331]
  • regularization for linear regression models. Multiple shrinkage priors are implemented that will shrink small regression ... overview in the preprint Shrinkage priors for Bayesian penalized regression. Note that only the full...
  • shrinkTVP

  • Referenced in 1 article [sw29787]
  • time-varying parameter models with shrinkage priors. Details on the algorithms used are provided...
  • blasso

  • Referenced in 13 articles [sw06769]
  • scale mixture of normal distributions. Prior distributions are proposed for the regularization parameters, resulting ... models that allows for adaptive, data-based shrinkage of the regression coefficients. Posterior inference ... addressed from a Bayesian perspective by assigning prior probabilities to all possible models. Corresponding computational...
  • BSGW

  • Referenced in 1 article [sw29207]
  • subjects. Bayesian Lasso shrinkage in the form of two Laplace priors - one for scale ... functions can be used to tune the shrinkage parameters. Monte Carlo Markov Chain (MCMC) sampling...
  • ashr

  • Referenced in 1 article [sw33933]
  • package ashr: Methods for Adaptive Shrinkage, using Empirical Bayes. The R package ’ashr’ implements ... likelihoods (e.g., normal, Poisson) and mixture priors (e.g., uniform, normal...
  • LSQR

  • Referenced in 358 articles [sw00530]
  • Algorithm 583: LSQR: Sparse Linear Equations and Least...
  • MapReduce

  • Referenced in 250 articles [sw00546]
  • MapReduce is a new parallel programming model initially...
  • Mathematica

  • Referenced in 5883 articles [sw00554]
  • Almost any workflow involves computing results, and that...
  • Matlab

  • Referenced in 12074 articles [sw00558]
  • MATLAB® is a high-level language and interactive...
  • Octave

  • Referenced in 284 articles [sw00646]
  • GNU Octave is a high-level language, primarily...
  • R

  • Referenced in 8359 articles [sw00771]
  • R is a language and environment for statistical...
  • RATS

  • Referenced in 16 articles [sw00780]
  • RATS (Regression Analysis of Time Series) is a...
  • WavBox 4

  • Referenced in 6 articles [sw01012]
  • WavBox 4.6 - A Software Toolbox for Wavelet Transforms...
  • EnKF

  • Referenced in 346 articles [sw02066]
  • EnKF-The Ensemble Kalman Filter The EnKF is...