Lmmhat {dbmss} R Documentation

## Estimation of the Lmm function

### Description

Estimates the Lmm function

### Usage

Lmmhat(X, r = NULL, ReferenceType = "", CheckArguments = TRUE)


### Arguments

 X A weighted, marked, planar point pattern (wmppp.object). r A vector of distances. If NULL, a sensible default value is chosen (512 intervals, from 0 to half the diameter of the window) following spatstat. ReferenceType One of the point types. Others are ignored. Default is all point types. CheckArguments Logical; if TRUE, the function arguments are verified. Should be set to FALSE to save time in simulations for example, when the arguments have been checked elsewhere.

### Details

Lmm is the normalized version of Kmm: Lmm(r)=\sqrt{\frac{Kmm}{\pi}}-r.

### Value

An object of class fv, see fv.object, which can be plotted directly using plot.fv.

### References

Penttinen, A., Stoyan, D. and Henttonen, H. M. (1992). Marked Point Processes in Forest Statistics. Forest Science 38(4): 806-824.

Espa, G., Giuliani, D. and Arbia, G. (2010). Weighting Ripley's K-function to account for the firm dimension in the analysis of spatial concentration. Discussion Papers, 12/2010. Universita di Trento, Trento: 26.

### See Also

Kmmhat, LmmEnvelope

### Examples

data(paracou16)
# Keep only 50% of points to run this example
X <- as.wmppp(rthin(paracou16, 0.5))
autoplot(X,
labelSize = expression("Basal area (" ~cm^2~ ")"),
labelColor = "Species")

# Calculate Lmm
r <- seq(0, 30, 2)
(Paracou <- Lmmhat(X, r))

# Plot
autoplot(Paracou)


[Package dbmss version 2.7-8 Index]