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Distance Based Measures of Spatial Structures

dbmss is an R package for simple computation of spatial statistic functions of distance to characterize the spatial structures of mapped objects, including classical ones (Ripley's K and others) and more recent ones used by spatial economists (Duranton and Overman's Kd, Marcon and Puech's M). It relies on spatstat for some core calculation.

Vignettes

A quick introduction is in vignette("dbmss").

A full documentation is available on the package website. It is a continuous update of the paper published in the Journal of Statistical Software (Marcon et al., 2015).

Reference

Marcon, E., Traissac, S., Puech, F. and Lang, G. (2015). Tools to Characterize Point Patterns: dbmss for R. Journal of Statistical Software. 67(3): 1-15.

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Install

install.packages('dbmss')

Monthly Downloads

755

Version

2.9-2

License

GNU General Public License

Issues

Pull Requests

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Repository

https://github.com/EricMarcon/dbmss/

Homepage

https://ericmarcon.github.io/dbmss/

Maintainer

Eric Marcon

Last Published

August 24th, 2024

Functions in dbmss (2.9-2)

Estimation of the confidence envelope of the Lmm function under its null hypothesis

Estimation of the confidence envelope of the L function under its null hypothesis

parallelCountNbd

Auxiliary functions to count point neighbors

Estimation of the L function

Distance Based Measures of Spatial Structures

rPopulationIndependenceM

Simulations of a point pattern according to the null hypothesis of population independence defined for M

spatstat generic functions

Methods for weighted, marked planar point patterns (of class wmppp) from spatstat

Estimation of the confidence envelope of the g function under its null hypothesis

ggplot methods to plot dbmss objects

dbmssEnvelope.object

Class of envelope of function values (fv)

rPopulationIndependenceK

Simulations of a point pattern according to the null hypothesis of population independence defined for K

Test whether an object is a weighted, marked, planar point pattern

envelope.Dtable

Computes simulation envelopes of a summary function.

Estimation of the g function

Estimation of the confidence envelope of the m function under its null hypothesis

Estimation of the M function

Spatial smoothing of individual dbmss's

Estimation of the confidence envelope of the M function under its null hypothesis

summary.dbmssEnvelope

Summary of a confidence envelope

Objects exported from other packages

rRandomLocation

Simulations of a point pattern according to the null hypothesis of random location

rRandomPositionK

Simulations of a point pattern according to the null hypothesis of random position defined for K

Converts data to class Dtable

Paracou field station plot 16, partial map

Converts data to class wmppp

Estimation of the m function

Create a Weighted, Marked, Planar Point Pattern

rRandomLabelingM

Simulations of a point pattern according to the null hypothesis of random labelling defined for M

print.dbmssEnvelope

Print a confidence envelope

rRandomLabeling

Simulations of a point pattern according to the null hypothesis of random labeling

Class of Weighted, Marked, Planar Point Patterns

CheckdbmssArguments

Checks the arguments of a function of the package dbmss

Estimation of the confidence envelope of the Kd function under its null hypothesis

Estimation of the D function

Goodness of Fit test between a distance based measure of spatial structure and simulations of its null hypothesis

Estimation of the confidence envelope of the D function under its null hypothesis

Create a Distance table object.

Estimation of the confidence envelope of the K function under its null hypothesis

Estimation of the Lmm function

Estimation of the K function

Estimation of the global confidence interval of simulations

Transform simulation values to an fv

Estimation of the Kd function

Estimation of the Kmm function

Estimation of the confidence envelope of the Kinhom function under its null hypothesis

Test of a point pattern against Complete Spatial Randomness

Estimation of the inhomogenous K function

Estimation of the confidence envelope of the Lmm function under its null hypothesis