• dlm

  • Referenced in 28 articles [sw04503]
  • analysis for linear regression models are reminded, and Markov chain Monte Carlo methods are presented...
  • StOpt

  • Referenced in 7 articles [sw32903]
  • dynamic programming methods based on Monte Carlo with regressions (global, local and sparse regressors ... methods are provided to solve by Monte Carlo some problems where the underlying stochastic state...
  • Statistics Toolbox

  • Referenced in 18 articles [sw10157]
  • regression or classification for predictive modeling, generate random numbers for Monte Carlo simulations, use statistical ... shrinkage, or use partial least squares regression. The toolbox provides supervised and unsupervised machine learning...
  • ESS++

  • Referenced in 4 articles [sw24089]
  • Bayesian variable selection for linear regression using evolutionary Monte Carlo. ESS++ is a C++ implementation ... approach for single and multiple response linear regression. ESS++ works well both when the number ... relevant predictors is based on evolutionary Monte Carlo. The C++ implementation of ESS++ is open...
  • SSS

  • Referenced in 31 articles [sw07794]
  • Large p” regression Model search in regression with very large numbers of candidate predictors raises ... standard approaches such as Markov chain Monte Carlo (MCMC) methods are often infeasible or ineffective ... aspects of performance characteristics in large-scale regression model searches. We also provide software implementing...
  • ROAST

  • Referenced in 7 articles [sw17318]
  • ROAST uses rotation, a Monte Carlo technology for multivariate regression. Since the number of rotations...
  • mlOSP

  • Referenced in 1 article [sw36181]
  • mlOSP: Towards a Unified Implementation of Regression Monte Carlo Algorithms. We introduce mlOSP, a computational ... presents a unified numerical implementation of Regression Monte Carlo (RMC) approaches to optimal stopping, providing ... well as in terms of machine learning regression modules. At the same time, mlOSP nests...
  • blasso

  • Referenced in 13 articles [sw06769]
  • regression coefficients. Posterior inference is easily achieved using Markov chain Monte Carlo (MCMC) methods. Uncertainty...
  • bcp

  • Referenced in 9 articles [sw14696]
  • using Markov Chain Monte Carlo. It also extends the methodology to regression models...
  • dynaTree

  • Referenced in 4 articles [sw07923]
  • design Inference by sequential Monte Carlo for dynamic tree regression and classification models with hooks...
  • GWmodel

  • Referenced in 4 articles [sw08531]
  • advanced GW regression fits and diagnostics; (iii) associated Monte Carlo significance tests for non-stationarity...
  • UNCSAM

  • Referenced in 4 articles [sw00990]
  • UNCSAM combines a Monte Carlo based approach (sampling and simulation) with regression- and correlation analysis...
  • zoib

  • Referenced in 4 articles [sw22966]
  • regression and obtains Bayesian Inference of the model via the Markov Chain Monte Carlo approach...
  • osDesign

  • Referenced in 6 articles [sw11936]
  • designs. Functions in this packages provides Monte Carlo based evaluation of operating characteristics such ... estimators of the components of a logistic regression model...
  • qregpd

  • Referenced in 1 article [sw32063]
  • estimate generalized quantile regressions using Markov Chain Monte Carlo methods or grid-search methods...
  • xtscc

  • Referenced in 7 articles [sw37339]
  • least-squares regression and fixed-effects (within) regression models with Driscoll and Kraay (Review ... standard errors. By running Monte Carlo simulations, I compare the finite-sample properties...
  • bayesQR

  • Referenced in 7 articles [sw11009]
  • package bayesQR: Bayesian quantile regression. Bayesian quantile regression using the asymmetric Laplace distribution, both continuous ... calculations, the Markov Chain Monte Carlo core of all algorithms is programmed in Fortran...
  • ASTRO-DF

  • Referenced in 7 articles [sw26833]
  • errors is designed to ensure that Monte Carlo effort within ASTRO-DF is sensitive ... question of using more complicated models, e.g., regression or stochastic kriging, in combination with adaptive ... iterates achieve the canonical Monte Carlo convergence rate, although a proof remains elusive...
  • BayesPostEst

  • Referenced in 1 article [sw31515]
  • quantities after estimating Bayesian regression models using Markov chain Monte Carlo (MCMC). Functionality includes...
  • GET

  • Referenced in 15 articles [sw35164]
  • envelopes can be used for graphical Monte Carlo and permutation tests where the test statistic ... prediction bands (e.g. confidence band in polynomial regression, Bayesian posterior prediction). See Myllymäki and Mrkvička...