
TISEAN
 Referenced in 139 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 likelihoodbased 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 SchnorrEuchner...

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 likelihoodbased dimension reduction in regression. Functions, methods, and data sets ... fitting likelihoodbased 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...

orthoDr
 Referenced in 1 article
[sw28510]
 Counting processbased dimension reduction methods for censored outcomes. We propose counting processbased dimension ... equations are constructed to estimate the dimension reduction subspace for the failure time model ... bias in estimating the dimension reduction subspace. Second, the nonparametric estimation involved adapts ... singular value decomposition to estimate the dimension reduction subspace. Numerical studies suggest that...

ACPCA
 Referenced in 1 article
[sw27101]
 simultaneously performs dimension reduction and adjustment for confounding variation. Dimension reduction methods are commonly applied ... propose ACPCA 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 opensource implementation is available...

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