Intrinsic Dimension Estimation

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Documentation for package ‘intrinsicDimension’ version 1.2.0

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addNoise Add Noise to Data Set
asPointwiseEstimator Turn a local estimator into a pointwise estimator
cornerPlane Corner Plane
cutHyperPlane Piece of Noisy Hyperplane
cutHyperSphere Piece of Noisy Hypersphere
dancoDimEst Dimension Estimation With the DANCo and MIND Methods
dnoiseGaussH Transition Functions Describing Noise
dnoiseNcChi Transition Functions Describing Noise
essLocalDimEst Expected Simplex Skewness Local Dimension Estimation
essReference ESS Reference Values
globalIntrinsicDimension Intrinsic Dimension Estimation
hill Dimension Estimation via Translated Poisson Distributions
hyperBall Isotropic Distributions With or Without Noise
hyperCube Hypercube
hyperCubeEdges Hypercube
hyperCubeFaces Hypercube
hyperSphere Isotropic Distributions With or Without Noise
hyperTwinPeaks Twin Peaks
intrinsicDimension Intrinsic Dimension Estimation and Data on Manifolds
isotropicNormal Isotropic Distributions With or Without Noise
knnDimEst Dimension Estimation from kNN Distances
localIntrinsicDimension Intrinsic Dimension Estimation
m14Manifold Manifolds from Rozza et al. (2012)
m15Manifold Manifolds from Rozza et al. (2012)
maxLikGlobalDimEst Dimension Estimation via Translated Poisson Distributions
maxLikLocalDimEst Dimension Estimation via Translated Poisson Distributions
maxLikPointwiseDimEst Dimension Estimation via Translated Poisson Distributions
mHeinManifold 12-dimensional manifold from Hein and Audibert (2005)
neighborhoods Obtaining neighborhoods (local data) from a data set
oblongNormal Oblong Normal Distribution
pcaLocalDimEst Local Dimension Estimation with PCA
pcaOtpmPointwiseDimEst Dimension Estimation With Optimally Topology Preserving Maps
pointwiseIntrinsicDimension Intrinsic Dimension Estimation
swissRoll Swiss roll with or without 3-sphere inside
swissRoll3Sph Swiss roll with or without 3-sphere inside
twinPeaks Twin Peaks