• CirCUs

  • Referenced in 9 articles [sw00128]
  • also describe a new decision variable selection heuristic that is based on recognizing that...
  • maSigPro

  • Referenced in 9 articles [sw11024]
  • expressed genes, and in second a variable selection strategy is applied to study differences between...
  • VarSelLCM

  • Referenced in 5 articles [sw15183]
  • VarSelLCM: Variable Selection for Model-Based Clustering using the Integrated Complete-Data Likelihood ... performing the cluster analysis with variable selection of continuous data by assuming independence between classes ... model interpretation and model selection. The variable selection is led by the Maximum Integrated Complete...
  • care

  • Referenced in 5 articles [sw19441]
  • High-Dimensional Regression and CAR Score Variable Selection. Implements the regression approach of Zuber ... Strimmer (2011) ”High-dimensional regression and variable selection using CAR scores” SAGMB ... score is a natural measure of variable importance and provides a canonical ordering of variables ... functions for estimating CAR scores, for variable selection using CAR scores, and for estimating corresponding...
  • bartMachine

  • Referenced in 8 articles [sw10962]
  • data analysis using BART such as variable selection, interaction detection, model diagnostic plots, incorporation...
  • PReMiuM

  • Referenced in 8 articles [sw14746]
  • implemented in the package as variable selection...
  • MixMoGenD

  • Referenced in 5 articles [sw08624]
  • Variable selection in model-based clustering using multilocus genotype data. We propose a variable selection...
  • spinyReg

  • Referenced in 4 articles [sw14821]
  • with Occam’s razor for Bayesian variable selection in high-dimensional regression. We address ... problem of Bayesian variable selection for high-dimensional linear regression. We consider a generative model ... state-of-the-art high-dimensional variable selection algorithms (such as lasso, adaptive lasso, stability ... slab procedures) are reported. Competitive variable selection results and predictive performances are achieved on both...
  • BAS

  • Referenced in 5 articles [sw24118]
  • package BAS: Bayesian Variable Selection and Model Averaging using Bayesian Adaptive Sampling. Package for Bayesian ... Variable Selection and Model Averaging in linear models and generalized linear models using stochastic ... Clyde (2015) . Other model selection criteria include AIC, BIC and Empirical Bayes estimates ... used. The user may force variables to always be included. Details behind the sampling algorithm...
  • SIS

  • Referenced in 5 articles [sw08182]
  • package SIS: SIS: Sure Independence Screening. Variable selection techniques are essential tools for model selection ... unified environment to carry out variable selection using iterative sure independence screening...
  • DALEX

  • Referenced in 7 articles [sw26094]
  • function of a single selected variable. It is a wrapper over packages ’pdp’ and ’ALEPlot...
  • ofw

  • Referenced in 4 articles [sw10549]
  • Package to Select Continuous Variables for Multiclass Classification with a Stochastic Wrapper Method. When dealing ... classification task. Few tools exist for selecting variables in such data sets, especially when classes ... continuous variables. The aim is to select relevant variables ... numerically evaluate the resulting variable selection. Two versions are proposed with the application of supervised...
  • cmenet

  • Referenced in 7 articles [sw21048]
  • method for bi-level variable selection of conditional main effects. This paper presents a novel...
  • GSPPCA

  • Referenced in 4 articles [sw25977]
  • Bayesian variable selection for globally sparse probabilistic PCA. Sparse versions of principal component analysis ... computed, the interpretation of the selected variables may be difficult since each axis ... allows the practitioner to identify which original variables are most relevant to describe the data ... Occam’s razor to select the relevant variables. Since the sparsity pattern is common...
  • GALGO

  • Referenced in 3 articles [sw25290]
  • GALGO: An R Package for Multivariate Variable Selection Using Genetic Algorithms. The development of statistical ... resources. It follows that an efficient variable selection strategy is required. However, although software packages ... performing univariate variable selection are available, a comprehensive software environment to develop and evaluate multivariate ... statistical models using a multivariate variable selection strategy is still needed. In order to address...
  • subselect

  • Referenced in 6 articles [sw06780]
  • package subselect: Selecting variable subsets. A collection of functions which (i) assess the quality...
  • cvplogistic

  • Referenced in 4 articles [sw29394]
  • Lasso-concave hybrid penalty for fast variable selection. The hybrid penalty applies the concave penalty ... only to the variables selected by the Lasso. For all the implemented methods, the solution...
  • ESS++

  • Referenced in 4 articles [sw24089]
  • Bayesian variable selection for linear regression using evolutionary Monte Carlo. ESS++ is a C++ implementation ... fully Bayesian variable selection approach for single and multiple response linear regression. ESS++ works well...
  • gvs_BUGS

  • Referenced in 4 articles [sw26317]
  • Gibbs Variable Selection using BUGS. In this paper we discuss and present in detail ... implementation of Gibbs variable selection as defined by Dellaportas et al. (2000, 2002) using...
  • BVSNLP

  • Referenced in 3 articles [sw22350]
  • package BVSNLP: Bayesian Variable Selection in High Dimensional Settings using Non-Local Prior. Variable/Feature selection ... priors to improve the performance of variable selection and coefficient estimation. It performs variable selection ... reports necessary outcomes of Bayesian variable selection such as Highest Posterior Probability Model (HPPM), Median...