marksum {ecespa} | R Documentation |
An exploratory data analysis technique for marked point patterns. The marked point pattern is mapped to a random field for visual inspection.
marksum(mippp, R = 10, nx = 30, ny = 30) ## S3 method for ploting objects of class 'ecespa.marksum': ## S3 method for class 'ecespa.marksum': plot(x, what="normalized", contour=FALSE, grid=FALSE, ribbon=TRUE,col=NULL ,main=NULL,xlab="",ylab="",...)
mippp |
A marked point pattern. An object with the ppp format of spatstat. |
R |
Radius. The distance argument r at which the mark-sum measure should be computed |
nx |
Grid density (for estimation) in the x-side. |
ny |
Grid density (for estimation) in the y-side. |
x |
An object of class 'ecespa.marksum' . Usually, the result of applying marksum to a point pattern. |
what |
What to plot. One of "marksum" (raw mark sum measure), "point" (point sum measure) or "normalized" (normalized sum measure). |
contour |
Logical; if "TRUE" add contour to map. |
grid |
Logical; if "TRUE" add marked grid to map. |
ribbon |
Logical; if "TRUE" add legend to map. |
col |
Color table to use for the map ( see help file on image for details). |
main |
Text or expression to add as a title to the plot. |
xlab |
Text or expression to add as a label to axis x. |
ylab |
Text or expression to add as a label to axis y. |
... |
Additional parameters to smooth.ppp , density.ppp or as.mask , to control
the parameters of the smoothing kernel, pixel resolution, etc. |
Penttinen (2006) defines the mark-sum measure as a smoothed summary measuring locally the contribution of points and marks. For any fixed location x within the observational window and a distance R, the mark-sum measure S[R](x) equals the sum of the marks of the points within the circle of radius R with centre in x. The point-sum measure I[R](x) is defined by him as the sum of points within the circle of radius R with centre in x, and describes the contribution of points locally near x. The normalized mark-sum measure describes the contribution of marks near x and is defined (Penttinen, 2006) as
S.normalized[R](x) = S[R](x)/I[R](x)
This implementation of marksum
estimates the mark-sum and the point-sum measures in a grid of points whose density is defined by nx
and
ny
.
marksum
gives an object of class 'ecespa.marksum'
; basically a list with the following elements:
normalized |
Normalized mark-sum measure estimated in the grid points. |
marksum |
Raw mark-sum measure estimated in the grid points. |
pointsum |
Point-sum measure estimated in the grid points. |
minus |
Point-sum of the grid points. For advanced use only. |
grid |
Grid of points. |
nx |
Density of the estimating grid in the x-side. |
ny |
Density of the estimating grid in the x-side. |
dataname |
Name of the ppp object analysed. |
R |
Radius. The distance argument r at which the mark-sum measure has been computed. |
window |
Window of the point pattern. |
plot.ecespa.marksum
plots the selected mark-sum measure.
Marcelino de la Cruz Rot marcelino.delacruz@upm.es
Penttinen, A. 2006. Statistics for Marked Point Patterns. In The Yearbook of the Finnish Statistical Society, pp. 70-91.
getis
, related to the point-sum measure, and markstats
for designing different implementations.
## Not run: data(seedlings1) seed.m <- marksum(seedlings1, R=25) plot(seed.m, what="marksum", sigma = 5) # raw mark-sum measure; sigma is bandwith for smoothing plot(seed.m, what="pointsum", sigma = 5, col = tim.colors(30),) # point sum measure plot(seed.m, what="normalized", dimyx=200, contour=TRUE, sigma = 5) # normalized mark-sum measure # the same with added grid plot(seed.m, what="normalized", dimyx=200, contour=TRUE, sigma = 5, grid=TRUE) # normalized mark-sum measure ## End(Not run)