spdensity: Kernel smoothed spatial density of point pattern In smacpod: Statistical Methods for the Analysis of Case-Control Point Data

Description

`spdensity` computes a kernel smoothed spatial density function from a point pattern. This function is basically a wrapper for `density.ppp`. The `density.ppp` function computes the spatial intensity of a point pattern; the `spdensity` function scales the intensity to produce a true spatial density.

Usage

 ```1 2 3 4``` ```spdensity(x, sigma = NULL, ..., weights = NULL, edge = TRUE, varcov = NULL, at = "pixels", leaveoneout = TRUE, adjust = 1, diggle = FALSE, kernel = "gaussian", scalekernel = is.character(kernel), positive = FALSE, verbose = TRUE) ```

Arguments

 `x` Point pattern (object of class `"ppp"`). `sigma` Standard deviation of isotropic smoothing kernel. Either a numerical value, or a function that computes an appropriate value of `sigma`. `...` Additional arguments passed to `pixellate.ppp` and `as.mask` to determine the pixel resolution, or passed to `sigma` if it is a function. `weights` Optional weights to be attached to the points. A numeric vector, numeric matrix, an `expression`, or a pixel image. `edge` Logical value indicating whether to apply edge correction. `varcov` Variance-covariance matrix of anisotropic smoothing kernel. Incompatible with `sigma`. `at` String specifying whether to compute the intensity values at a grid of pixel locations (`at="pixels"`) or only at the points of `x` (`at="points"`). `leaveoneout` Logical value indicating whether to compute a leave-one-out estimator. Applicable only when `at="points"`. `adjust` Optional. Adjustment factor for the smoothing parameter. `diggle` Logical. If `TRUE`, use the Jones-Diggle improved edge correction, which is more accurate but slower to compute than the default correction. `kernel` The smoothing kernel. A character string specifying the smoothing kernel (current options are `"gaussian"`, `"epanechnikov"`, `"quartic"` or `"disc"`), or a pixel image (object of class `"im"`) containing values of the kernel, or a `function(x,y)` which yields values of the kernel. `scalekernel` Logical value. If `scalekernel=TRUE`, then the kernel will be rescaled to the bandwidth determined by `sigma` and `varcov`: this is the default behaviour when `kernel` is a character string. If `scalekernel=FALSE`, then `sigma` and `varcov` will be ignored: this is the default behaviour when `kernel` is a function or a pixel image. `positive` Logical value indicating whether to force all density values to be positive numbers. Default is `FALSE`. `verbose` Logical value indicating whether to issue warnings about numerical problems and conditions.

Value

This function produces the spatial density of `x` as an object of class `im` from the `spatstat` package.

Joshua French

References

Waller, L.A. and Gotway, C.A. (2005). Applied Spatial Statistics for Public Health Data. Hoboken, NJ: Wiley.

`density.ppp`
 ```1 2``` ```data(grave) contour(spdensity(grave)) ```