dbmss (version 1.2.4)

Lmm.r: Estimation of the Lmm function

Description

Estimates the Lmm function

Usage

Lmm.r(X, r, ReferenceType = "")

Arguments

X

A point pattern (ppp.object), marks must be a dataframe with two columns: PointType: labels, as factors. PointWeight: weights.

r

A vector of distances.

ReferenceType

One of the point types. Others are ignored. Default is all point types.

Value

• A vector containing Lmm(r) values.

Details

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

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

Kmm.r, LmmEnvelope

Examples

data(paracou16)
# Keep only 50% of points to run this example
X <- rthin(paracou16, 0.5)
plot(X)

# Calculate Lmm
r <- seq(0, 30, 2)
ActualValues.X <- Lmm.r(X, r)

# Plot
PlotResults(r, ActualValues.X, ylab="Lmm", ReferenceValue=0)