Hns {ks} | R Documentation |
Normal scale bandwidth.
Hns(x, deriv.order=0) hns(x, deriv.order=0) Hns.kcde(x) hns.kcde(x)
x |
vector/matrix of data values |
deriv.order |
derivative order |
Hns
is equal to (4/(n*(d+2*r+2)))^(2/(d+2*r+4))*var(x)
,
n = sample size, d = dimension of data, r = derivative
order. hns
is the analogue of Hns
for 1-d data. These
can be used for density (derivative) estimators
kde
, kdde
.
The equivalents for distribution estimators kcde
are
Hns.kcde
and hns.code
.
Full normal scale bandwidth matrix.
Chacon J.E., Duong, T. & Wand, M.P. (2011). Asymptotics for general multivariate kernel density derivative estimators. Statistica Sinica. 21, 807-840.
x <- rmvnorm.mixt(1000) Hns(x, deriv.order=1) hns(x[,1], deriv.order=1)