bw_balloon_LQ: Loftsgaarden-Quesenberry kth nearest neighbor bandwidths

Description Usage Arguments Details Value Examples

Description

bw_balloon_LQ looks for the bandwidth following the Loftsgaarden-Quesenberry algorithm. The bandwidth depends on the point of estimation.

Usage

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bw_balloon_LQ(tdat, edat, k)

Arguments

tdat

vector or array containing the training dataset.

edat

vector or array containing the evaluation data points.

k

integer specifying the order of the neighbor.

Details

These are the details of the function.

Value

a vector of bandwidths (one bandwidth per evaluation data point)

Examples

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# univariate
bw_balloon_LQ(tdat = 1:10,edat = 5.1,k = 3)
bw_balloon_LQ(tdat = 1:10,edat = c(2.8,5.1),k = 3)
# multivariate
bw_balloon_LQ(tdat = array(1:20,dim=c(4,5)),edat = 1:4,k = 1)

kcucchi/vdke documentation built on May 20, 2019, 8:28 a.m.