• TISEAN

  • Referenced in 138 articles [sw00967]
  • algorithms for data representation, prediction, noise reduction, dimension and Lyapunov estimation, and nonlinearity testing...
  • Leibniz

  • Referenced in 31 articles [sw12871]
  • data estimation by a lazy learner - dimension reduction of models - decomposition of graphs and matrices...
  • Algorithm 913

  • Referenced in 21 articles [sw12775]
  • based on the induced dimension reduction theorem, that provides a way to construct subsequent residuals...
  • SADE

  • Referenced in 14 articles [sw07076]
  • ordinary differential equations, order and dimension reductions using Lie symmetries, classification of differential equations, Casimir...
  • GAP

  • Referenced in 12 articles [sw26294]
  • effective than conventional graphical methods when dimension reduction techniques fail or when data...
  • dr

  • Referenced in 8 articles [sw14718]
  • Methods for Dimension Reduction for Regression. Functions, methods, and datasets for fitting dimension reduction regression ... code for computing permutation tests of dimension. Adding additional methods of estimating dimension is straightforward...
  • LDR

  • Referenced in 11 articles [sw08893]
  • proposed likelihood-based methods for sufficient dimension reduction. Current capabilities include estimation of reduced subspaces...
  • BKZ

  • Referenced in 44 articles [sw10242]
  • best lattice reduction algorithm known in practice for high dimension is Schnorr-Euchner...
  • HDclassif

  • Referenced in 9 articles [sw11114]
  • model which combines the ideas of dimension reduction and constraints on the model...
  • edrGraphicalTools

  • Referenced in 8 articles [sw11105]
  • edrGraphicalTools: Provides tools for dimension reduction methods. This package comes to illustrate the articles ... selecting the number of slices and the dimension of the model in SIR and SAVE...
  • ldr

  • Referenced in 5 articles [sw16971]
  • package ldr: Methods for likelihood-based dimension reduction in regression. Functions, methods, and data sets ... fitting likelihood-based dimension reduction in regression, using principal fitted components (pfc), likelihood acquired directions...
  • Geoxp

  • Referenced in 6 articles [sw08289]
  • data, GeoXp includes some dimension reduction techniques such...
  • curvclust

  • Referenced in 5 articles [sw07435]
  • random effects. We propose an efficient dimension reduction step based on wavelet thresholding adapted...
  • LDRTools

  • Referenced in 2 articles [sw19809]
  • package LDRTools: Tools for Linear Dimension Reduction. Linear dimension reduction subspaces can be uniquely defined...
  • WavePacket

  • Referenced in 3 articles [sw19829]
  • focus on open quantum systems and dimension reduction; it also describes the codes for optimal...
  • AC-PCA

  • Referenced in 1 article [sw27101]
  • simultaneously performs dimension reduction and adjustment for confounding variation. Dimension reduction methods are commonly applied ... propose AC-PCA for simultaneous dimension reduction and adjustment for confounding variation. We show that...
  • sSDR

  • Referenced in 1 article [sw20968]
  • Structured ordinary least squares: a sufficient dimension reduction approach for regressions with partitioned predictors ... this known structure in the predictor dimension reduction stage that precedes modeling ... this, we propose a novel Sufficient Dimension Reduction (SDR) approach that we call {it structured...
  • ePCA

  • Referenced in 2 articles [sw27830]
  • used very generally for dimension reduction and denoising of large data matrices with exponential family ... Marchenko – Pastur law in high dimensions. An open-source implementation is available...
  • GSVA

  • Referenced in 2 articles [sw17293]
  • single gene analysis include noise and dimension reduction, as well as greater biological interpretability...
  • MLC Toolbox

  • Referenced in 1 article [sw28399]
  • many combinations of feature space dimension reduction, sample clustering, label space dimension reduction and ensemble...