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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

641

Version

2.7-6

License

GNU General Public License

Issues

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Repository

https://github.com/EricMarcon/dbmss

Maintainer

Eric Marcon

Last Published

June 4th, 2021

Functions in dbmss (2.7-6)

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

Estimation of the M function

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

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

Create a Distance table object.

Converts data to class wmppp

Estimation of the K function

Estimation of the D function

Transform simulation values to an fv

envelope.Dtable

Computes simulation envelopes of a summary function.

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

ggplot methods to plot dbmss objects

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

Estimation of the Kd function

Estimation of the L function

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

rPopulationIndependenceK

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

print.dbmssEnvelope

Print a confidence envelope

Estimation of the global confidence interval of simulations

parallelCountNbd

Auxiliary functions to count point neighbors

Create a Weighted, Marked, Planar Point Pattern

Class of Weighted, Marked, Planar Point Patterns

Estimation of the Lmm function

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

Distance Based Measures of Spatial Structures

dbmssEnvelope.object

Class of envelope of function values (fv)

spatstat generic functions

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

Converts data to class Dtable

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

Estimation of the g function

rPopulationIndependenceM

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

rRandomLabeling

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

Estimation of the inhomogenous K function

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

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

Estimation of the m function

rRandomPositionK

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

summary.dbmssEnvelope

Summary of a confidence envelope

rRandomLocation

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

Paracou field station plot 16, partial map

rRandomLabelingM

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

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

CheckdbmssArguments

Checks the arguments of a function of the package dbmss

Estimation of the Kmm function

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

Test of a point pattern against Complete Spatial Randomness