bw_balloon_LQ: Loftsgaarden-Quesenberry kth nearest neighbor bandwidths
In kcucchi/vdke: Variable Kernel Density Estimation methods

Description Usage Arguments Details Value Examples

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

1	bw_balloon_LQ(tdat, edat, k)

`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.

These are the details of the function.

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

# 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)