Functions for Spatial Point Pattern Analysis


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Documentation for package ‘ecespa’ version 1.1-17

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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