neighborhood: Symmetric neighborhoods for kernel smoothing
Description
Nearest neighborhoods for the values of a continuous predictor. The
result is used for the conditional Kaplan-Meier estimator
and other conditional product limit estimators.
Usage
neighborhood(x, bandwidth = NULL, kernel = "box")
Arguments
x
Numeric vector -- typically the observations of a continuous
random variate.
bandwidth
Controls the distance between neighbors in a
neighborhood. It can be a decimal, i.e. the bandwidth, or the string
`"smooth"', in which case the fourth root of the sample
size is used, or NULL in which case the
kernel
Only the rectangular kernel ("box") is implemented.
Value
An object of class 'neighborhood'.
The value is a list that includes the unique values of `x'
(values) for which a neighborhood, consisting of the nearest neighbors, is defined by
the first neighbor (first.nbh) of the usually very long
vector neighbors
and the size of the neighborhood (size.nbh).
Further values are the arguments bandwidth, kernel, the total sample
size n and the number of unique values nu.
References
Stute, W. "Asymptotic Normality of Nearest Neighbor Regression Function
Estimates", The Annals of Statistics,
1984,12,917--926.
##---- Should be DIRECTLY executable !! ----##-- ==> Define data, use random,##-- or do help(data=index) for the standard data sets.library(survival)
data(pbc)
neighborhood(pbc$age)