rbox: Local Regression, Likelihood and Density Estimation.
Description
rbox() is used to specify a rectangular box evaluation
structure for locfit.raw(). The structure begins
by generating a bounding box for the data, then recursively divides
the box to a desired precision.
Usage
rbox(cut=0.8, type="tree", ll, ur)
Arguments
type
If type="tree", the cells are recursively divided according to
the bandwidths at each corner of the cell; see Chapter 11 of Loader (1999).
If type="kdtree", the K-D tree structure used in Loess
(Cleveland and Grosse, 1991) is used.
cut
Precision of the tree; a smaller value of cut results in a
larger tree with more nodes being generated.
ll
Lower left corner of the initial cell. Length should be the number
of dimensions of the data provided to locfit.raw().
ur
Upper right corner of the initial cell. By default, ll and
ur are generated as the bounding box for the data.
References
Loader, C. (1999). Local Regression and Likelihood. Springer, New York.
Cleveland, W. and Grosse, E. (1991). Computational Methods for Local
Regression. Statistics and Computing 1.