• CMA-ES

  • Referenced in 109 articles [sw05063]
  • stands for Covariance Matrix Adaptation Evolution Strategy. Evolution strategies (ES) are stochastic, derivative-free methods ... variation (via mutation and recombination) and selection: in each generation (iteration) new individuals (candidate solutions ... stochastic way, and then some individuals are selected for the next generation based on their ... variables in this distribution are represented by a covariance matrix. The covariance matrix adaptation...
  • foba

  • Referenced in 27 articles [sw35840]
  • package foba - greedy variable selection. foba is a package that implements forward, backward, and foba ... ridge regression, described in the paper ”Adaptive Forward-Backward Greedy Algorithm for Learning Sparse Representations...
  • BAS

  • Referenced in 5 articles [sw24118]
  • Model Averaging using Bayesian Adaptive Sampling. Package for Bayesian Variable Selection and Model Averaging...
  • ConvexLAR

  • Referenced in 2 articles [sw16543]
  • extends to group selection and data adaptive variable selection. After simple modification, it also yields...
  • BayesTree

  • Referenced in 59 articles [sw07995]
  • nonparametric Bayesian regression approach which uses dimensionally adaptive random basis elements. Motivated by ensemble methods ... also be used for model-free variable selection. BART’s many features are illustrated with...
  • spinyReg

  • Referenced in 4 articles [sw14821]
  • high-dimensional variable selection algorithms (such as lasso, adaptive lasso, stability selection or spike...
  • cqrReg

  • Referenced in 3 articles [sw21332]
  • Quantile and Composite Quantile Regression and Variable Selection. The cqrReg package ... with and without an adaptive lasso penalty for variable selection. In this paper, we reformulate...
  • decon

  • Referenced in 19 articles [sw11088]
  • nonparametric regression model with errors-in-variables. The R functions allow the measurement errors ... estimators computationally more efficient in R, we adapt the ”Fast Fourier Transform” (FFT) algorithm ... deconvolution kernel estimation. Several methods for the selection of the data-driven smoothing parameter...
  • DBKGrad

  • Referenced in 5 articles [sw14541]
  • considered as a discrete variable. The bandwidth, fixed or adaptive, is allowed to be manually ... given by the user or selected by cross-validation. Pointwise confidence intervals, for each considered...
  • AdapEnetClass

  • Referenced in 1 article [sw16165]
  • Adaptive Elastic Net Methods for Censored Data. Provides new approaches to variable selection...
  • cvplogistic

  • Referenced in 4 articles [sw29394]
  • approximation by coordinate descant (LLA-CD) and adaptive rescaling algorithms for computing the solutions ... Lasso-concave hybrid penalty for fast variable selection. The hybrid penalty applies the concave penalty...
  • SelvarMix

  • Referenced in 3 articles [sw24498]
  • variable selection in the model-based clustering and classification frameworks. First, the variables are arranged ... /j.csda.2009.04.013>, is adapted to define the role of variables...
  • SpatialVS

  • Referenced in 1 article [sw31495]
  • Selection. Perform variable selection for the spatial Poisson regression model under the adaptive elastic...
  • NonpModelCheck

  • Referenced in 1 article [sw15235]
  • nonparametric regression model and a variable (or group) selection procedure based on False Discovery Rate ... automatically chosen by cross validation or an adaptive procedure...
  • ACGSSV

  • Referenced in 9 articles [sw20836]
  • self-scaling memoryless BFGS update. An accelerated adaptive class of nonlinear conjugate gradient algorithms ... different structure and complexity, we prove that selection of the scaling parameter in self-scaling ... test problem collection with variables, we show that the adaptive Perry conjugate gradient algorithms based...
  • FindIt

  • Referenced in 2 articles [sw08164]
  • proposed method is applicable, for example, when selecting a small number of most (or least ... treatment of interest. The method adapts the Support Vector Machine classifier by placing separate LASSO ... other parameters, thereby making the variable selection suitable for the exploration of causal heterogeneity...
  • MiRAnorm

  • Referenced in 0 articles [sw17554]
  • adaptive normalization algorithm that selects housekeeping genes based on the sample level variability ... Genome Biology under “MiRA-norm: An Adaptive Method for the Normalization of MicroRNA Array Data...
  • Kubios HRV

  • Referenced in 2 articles [sw29196]
  • easy to use software for heart rate variability (HRV) analysis. The software supports several input ... adaptive QRS detection algorithm and tools for artifact correction, trend removal and analysis sample selection...
  • Adaptive Threshold

  • Referenced in 1 article [sw34284]
  • Adaptive Thresholding in Structure Learning of a Bayesian Network. Thresholding a measure in conditional independence ... sensitive to the threshold that is commonly selected: 1) arbitrarily; 2) irrespective of characteristics ... degree of variable dependence, and variables’ cardinalities. Following, we suggest to adaptively threshold individual tests...
  • SIVREG

  • Referenced in 1 article [sw37425]
  • invalid instruments. sivreg estimates a linear instrumental variables regression where some of the instruments fail ... from a 2SLS regression applying the (adaptive) Lasso selection. For general information about adaptive Lasso...