delt (version 0.8.2)

Estimation of Multivariate Densities Using Adaptive Partitions

Description

We implement methods for estimating multivariate densities. We include a discretized kernel estimator, an adaptive histogram (a greedy histogram and a CART-histogram), stagewise minimization, and bootstrap aggregation.

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Install

install.packages('delt')

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Version

0.8.2

License

GPL (>= 2)

Maintainer

Jussi Klemela

Last Published

June 3rd, 2015

Functions in delt (0.8.2)

eval.bagg

Returns a bootstrap aggregation of adaptive histograms

lefrig2par

Transforms an evaluation tree so that it can be plotted with the "plottree" function of package "denpro"

lstseq.greedy

Calculates a scale of greedy histograms

intpcf

Calculates the integral of a piecewise constant function

plotparti

Draws a partition

delt-package

Estimation of Multivariate Densities Using Adaptive Partitions

eval.greedy

Returns a greedy histogram

eval.pick

Returns a subtree of an evaluation tree

lstseq.bagg

Calculates a scale of bootstrap aggregated histograms

prune

Prepares for pruning an overfitting evaluation tree

supp

Returns the bounding box of observations

cluster.lst

Assigns labels to data points

lstseq.cart

Calculates a scale of CART histograms

eval.stage

Returns a stagewise minimization estimate

densplit

Calculation of an overfitting histogram

scaspa

Finds the number of modes of histograms which are obtained by pruning an overfitting histogram

eval.stage.gauss

Returns a 1D Gaussian mixture density estimate

pcf.greedy.kernel

Computes a discretized kernel estimator with an adaptive partition

partition

Finds the partition generated by an evaluation tree

makebina

Tranforms and evaluation tree to the tree object of R

eval.cart

Calculates a CART histogram