R: Functions for Spatial Point Pattern Analysis

# Functions for Spatial Point Pattern Analysis

## Documentation for package ‘ecespa’ version 1.1-18

- DESCRIPTION file.

## Help Pages

ecespa-package | Functions for spatial point pattern analysis in ecology
dixon2002 | Dixon (2002) Nearest-neighbor contingency table analysis
ecespa | Functions for spatial point pattern analysis in ecology
ecespa.kci | Test against non-Poisson (in-)homogeneous models
ecespa.kmm | Mark-weighted K-function
ecespa.minconfit | Fit the (In)homogeneous Poisson Cluster Point Process by Minimum Contrast
fig1 | Artificial point data.
fig2 | Artificial point data.
fig3 | Artificial point data.
figuras | Artificial point data.
getis | Neighbourhood density function
gypsophylous | Spatial point pattern of a plant community
haz.ppp | Easily convert xy data to ppp format
Helianthemum | Spatial point pattern of Helianthemum squamatum adult plants and seedlings
ipc.estK | Fit the (In)homogeneous Poisson Cluster Point Process by Minimum Contrast
K012 | Tests against 'independent labelling'
K1K2 | Differences between univariate and bivariate K-functions
Kci | Test against non-Poisson (in-)homogeneous models
Kclust | Fit the Poisson Cluster Point Process by Minimum Contrast
Ki | Test against non-Poisson (in-)homogeneous models
Kinhom.log | Simulation envelopes from the fitted values of a logistic model
Kmm | Mark-weighted K-function
Kmulti.ls | Lotwick's and Silverman's combined estimator of the marked K-function
LF.gof | Loosmore and Ford Goodness of Fit Test
marksum | Mark-sum measure
p2colasr | P-value for a discrete distribution on small sample data
pc.estK | Fit the Poisson Cluster Point Process by Minimum Contrast
plot.ecespa.getis | Neighbourhood density function
plot.ecespa.kci | Test against non-Poisson (in-)homogeneous models
plot.ecespa.kmm | Mark-weighted K-function
plot.ecespa.marksum | Mark-sum measure
plot.ecespa.minconfit | Fit the (In)homogeneous Poisson Cluster Point Process by Minimum Contrast
plot.ecespa.syrjala | Syrjala's test for the difference between the spatial distributions of two populations
plot.syrjala.test | Syrjala's test for the difference between the spatial distributions of two populations
print.ecespa.getis | Neighbourhood density function
print.ecespa.kci | Test against non-Poisson (in-)homogeneous models
print.ecespa.kmm | Mark-weighted K-function
print.ecespa.marksum | Mark-sum measure
print.ecespa.minconfit | Fit the (In)homogeneous Poisson Cluster Point Process by Minimum Contrast
print.ecespa.syrjala | Syrjala's test for the difference between the spatial distributions of two populations
print.syrjala.test | Syrjala's test for the difference between the spatial distributions of two populations
quercusvm | Alive and dead oak trees
rIPCP | Simulate Inhomogeneous Poisson Cluster Process
seedlings | Cohorts of Helianthemum squamatum seedlings
seedlings1 | Cohorts of Helianthemum squamatum seedlings
seedlings2 | Cohorts of Helianthemum squamatum seedlings
sim.poissonc | Simulate Poisson Cluster Process
swamp | Tree Species in a Swamp Forest
syr1 | Syrjala test data
syr2 | Syrjala test data
syr3 | Syrjala test data
syrjala | Syrjala's test for the difference between the spatial distributions of two populations
syrjala.test | Syrjala's test for the difference between the spatial distributions of two populations
syrjala0 | Syrjala's test for the difference between the spatial distributions of two populations