hexDensity: Kernel Density Estimation with Hexagonal grid.

In hexDensity: Fast Kernel Density Estimation with Hexagonal Grid

Kernel Density Estimation with Hexagonal grid.

Description

Kernel Density Estimation with Hexagonal grid.

Usage

hexDensity(
  x,
  y = NULL,
  xbins = 128,
  bandwidth = NULL,
  edge = TRUE,
  diggle = FALSE,
  weight = NULL,
  ...
)

Arguments

x, y	Coords of the points or a single plotting structure to be used in binning. See xy.coords.
xbins	Number of bins in a row.
bandwidth	Bandwidth for the smoothing kernel. Either a scalar, a vector of length 2, or a 2x2 variance-covariance matrix for the bandwidths in the x and y directions.
edge	Logical value for whether to apply edge correction. Default is TRUE.
diggle	Logical value for apply edge correction with the more accurate Jones-Diggle method (need 'edge' to be TRUE).
weight	numeric weight vector to be assigned to points.
...	arguments for hexbinFull

Details

Default bandwidth is the normal scale bandwidth selector n^(-1/3)*var where n is sample size and var is the variance-covariance matrix.

Value

an S4 object of class hexbin.

References

Diggle, P. J. (2010) Nonparametric methods. Chapter 18, pp. 299–316 in A.E. Gelfand, P.J. Diggle, M. Fuentes and P. Guttorp (eds.) Handbook of Spatial Statistics, CRC Press, Boca Raton, FL.

Jones, M. C. (1993) Simple boundary corrections for kernel density estimation. Statistics and Computing 3, 135–146.

Examples

set.seed(133)
d = hexDensity(x=rnorm(200),y=rnorm(200))

hexDensity documentation built on June 8, 2025, 1:10 p.m.