dpill(x, y, blockmax=5, divisor=20, trim=0.01, proptrun=0.05, gridsize=401, range.x=<<see below>>, truncate=T)
x
| vector of x data. Missing values are not accepted. |
y
|
vector of y data.
This must be same length as x , and
missing values are not accepted.
|
blockmax
| the maximum number of blocks of the data for construction of an initial parametric estimate. |
divisor
| the value that the sample size is divided by to determine a lower limit on the number of blocks of the data for construction of an initial parametric estimate. |
trim
|
the proportion of the sample trimmed from each end in the
x direction before application of the plug-in methodology.
|
proptrun
|
the proportion of the range of x at each end truncated in the
functional estimates.
|
gridsize
| number of equally-spaced grid points over which the function is to be estimated. |
range.x
|
vector containing the minimum and maximum values of x at which to
compute the estimate.
For density estimation the default is the minimum and maximum data values
with 5% of the range added to each end.
For regression estimation the default is the minimum and maximum data values.
|
truncate
|
logical flag: if TRUE , data with x values outside the range specified
by range.x are ignored.
|
x
values then the local polynomial smooths required for the
bandwidth selection algorithm may become degenerate and the function
will crash. Outliers in the y
direction may lead to deterioration
of the quality of the selected bandwidth.Wand, M. P. and Jones, M. C. (1995). Kernel Smoothing. Chapman and Hall, London.
ksmooth
, locpoly
.data(geyser) x <- geyser$duration y <- geyser$waiting plot(x,y) h <- dpill(x,y) fit <- locpoly(x,y,bandwidth=h) lines(fit)