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ks: Kernel Density Estimation and Kernel Discriminant Analysis for Multivariate Data in R
We introduce a new R package ks for multivariate kernel smoothing. Expand
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Plug-in bandwidth matrices for bivariate kernel density estimation
We consider bandwidth matrix selection for bivariate kernel density estimators. The majority of work in this area has been directed towards selection of diagonal bandwidth matrices, but fullExpand
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Cross-validation bandwidth matrices for multivariate kernel density estimation
The performance of multivariate kernel density estimates depends crucially on the choice of bandwidth matrix, but progress towards developing good bandwidth matrix selectors has been relatively slow.Expand
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We investigate kernel estimators of multivariate density derivative func- tions using general (or unconstrained) bandwidth matrix selectors. These density derivative estimators have been relativelyExpand
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Multivariate plug-in bandwidth selection with unconstrained pilot bandwidth matrices
Multivariate kernel density estimation is an important technique in exploratory data analysis. Its utility relies on its ease of interpretation, especially by graphical means. The crucial factorExpand
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Feature significance for multivariate kernel density estimation
This paper proposes a framework for feature significance in d-dimensional data which combines kernel density derivative estimators and hypothesis tests for modal regions. Expand
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Data-driven density derivative estimation, with applications to nonparametric clustering and bump hunting
Important information concerning a multivariate data set, such as clusters and modal regions, is contained in the derivatives of the probability density function. Despite this importance,Expand
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Multivariate Kernel Smoothing and Its Applications
Preface List of Figures List of Tables List of Algorithms Introduction Exploratory data analysis with density estimation Exploratory data analysis with density derivatives estimationExpand
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Convergence rates for unconstrained bandwidth matrix selectors in multivariate kernal density estimation
Progress in selection of smoothing parameters for kernel density estimation has been much slower in the multivariate than univariate setting. Within the context of multivariate density estimationExpand
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Descriptive and experimental analysis of the dispersion of neural crest cells along the dorsolateral path and their entry into ectoderm in the chick embryo.
We have characterized the dispersion of neural crest cells along the dorsolateral path in the trunk of the chicken embryo and experimentally investigated the control of neural crest cell entry intoExpand
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