The code implements an approximation of the multivariate bandwidth calculation from [1]. In contrast to other multivariate bandwidth estimators, it can be estimated from a preclustered sample distribution offering a simple way of estimating compact and accurate KDEs with variable kernels.

C_code
......\compileBWcalc.m
......\mex_getIntSquaredHessian.cpp
......\output
checkcompiledBWestimator.m
demoBW_Estimation.m
demoBW_Estimation1D.m
demoBW_with_preclustering.m
drawTools
.........\cols.m
.........\col_sum.m
.........\conf2mahal.m
.........\constructKDE.m
.........\drawDistributionGMM.m
.........\draw_ellipse.m
.........\draw_ellipse_axes.m
.........\evaluateDistributionAt.m
.........\evaluatePointsUnderPdf.m
.........\gaussian_prob.m
.........\getAllSigmaPoints.m
.........\getAllSigmaPointsOnMixture.m
.........\normmixpdf.m
.........\normpdfmy.m
.........\plotcov2.m
.........\plotcov3.m
.........\plotgauss1d.m
.........\plotgauss2d.m
.........\plot_arrow.m
.........\process_options.m
.........\rows.m
.........\showDecomposedPdf.m
.........\sqdist.m
.........\visualizeKDE.m
.........\visualizePdf2d2.m
.........\visualizePdfImage.m
estimateBandwidth.m
getBWfromStruct.m
license.txt
ndDirectPlugin_JointClean.m
readme.txt
tools
.....\applyForScaleTransformToPdf.m
.....\applyInvScaleTransformToPdf.m
.....\momentMatchPdf.m
visualizeEstimation.m

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