dpih(x, scalest="minim", level=2, gridsize=401, range.x=range(x), truncate=F)
x
| vector containing the sample on which the histogram is to be constructed. |
scalest
|
estimate of scale.
|
level
| number of levels of functional estimation used in the plug-in rule. |
gridsize
| number of grid points used in the binned approximations to functional estimates. |
range.x
| range over which functional estimates are obtained. The default is the minimum and maximum data values. |
truncate
|
if truncate is TRUE then observations outside
of the interval specified by range.x are omitted.
Otherwise, they are used to weight the extreme grid points.
|
Sheather, S. J. and Jones, M. C. (1991). A reliable data-based bandwidth selection method for kernel density estimation. Journal of the Royal Statistical Society, Series B, 53, 683-690.
Wand, M. P. (1995). Data-based choice of histogram binwidth. University of New South Wales, Australian Graduate School of Management Working Paper Series No. 95-011.
hist
data(geyser) x <- geyser$duration h <- dpih(x) bins <- seq(min(x)-0.1,max(x)+0.1+h,by=h) hist(x,breaks=bins)