• TISEAN

  • Referenced in 121 articles [sw00967]
  • algorithms for data representation, prediction, noise reduction, dimension and Lyapunov estimation, and nonlinearity testing...
  • Leibniz

  • Referenced in 30 articles [sw12871]
  • data estimation by a lazy learner - dimension reduction of models - decomposition of graphs and matrices...
  • Algorithm 913

  • Referenced in 15 articles [sw12775]
  • based on the induced dimension reduction theorem, that provides a way to construct subsequent residuals...
  • SADE

  • Referenced in 12 articles [sw07076]
  • ordinary differential equations, order and dimension reductions using Lie symmetries, classification of differential equations, Casimir...
  • dr

  • Referenced in 4 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...
  • BKZ

  • Referenced in 25 articles [sw10242]
  • best lattice reduction algorithm known in practice for high dimension is Schnorr-Euchner...
  • LDR

  • Referenced in 5 articles [sw08893]
  • proposed likelihood-based methods for sufficient dimension reduction. Current capabilities include estimation of reduced subspaces...
  • edrGraphicalTools

  • Referenced in 5 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...
  • LDRTools

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

  • Referenced in 2 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...
  • 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...
  • HDclassif

  • Referenced in 2 articles [sw11114]
  • model which combines the ideas of dimension reduction and constraints on the model...
  • WavePacket

  • Referenced in 2 articles [sw19829]
  • focus on open quantum systems and dimension reduction; it also describes the codes for optimal...
  • curvclust

  • Referenced in 2 articles [sw07435]
  • random effects. We propose an efficient dimension reduction step based on wavelet thresholding adapted...
  • EDR

  • Referenced in 1 article [sw08172]
  • Estimation of the effective dimension reduction (EDR) space. The library contains R-functions to estimate ... effective dimension reduction space in multi-index regression models...
  • lfda

  • Referenced in 1 article [sw20801]
  • popular for supervised dimensionality reduction method. lfda is an R package for performing local Fisher ... visualization functions to easily visualize the dimension reduction results by using either...
  • multiDimBio

  • Referenced in 1 article [sw19778]
  • through publication. The methods focus on dimension reduction approaches to detect patterns in complex, multivariate...
  • Geoxp

  • Referenced in 1 article [sw08289]
  • data, GeoXp includes some dimension reduction techniques such...
  • ICLUS

  • Referenced in 1 article [sw02611]
  • patterns. ICA is also a useful dimension reduction technique for multivariate data analysis. We apply...
  • SIMLR

  • Referenced in 1 article [sw19471]
  • used to perform tasks such as dimension reduction, clustering, and visualization of heterogeneous populations...