Learn R Programming

⚠️There's a newer version (2.9-2) of this package.Take me there.

dbmss (version 2.3-0)

Distance-Based Measures of Spatial Structures

Description

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). Relies on spatstat for some core calculation.

Copy Link

Version

Install

install.packages('dbmss')

Monthly Downloads

755

Version

2.3-0

License

GNU General Public License

Maintainer

Eric Marcon

Last Published

September 18th, 2016

Functions in dbmss (2.3-0)

Estimation of the D function

Converts data to class Dtable

Distance Based Measures of Spatial Structures

dbmssEnvelope.object

Class of envelope of function values (fv)

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

Transform simulation values to an fv

envelope.Dtable

Computes simulation envelopes of a summary function.

Create a Distance table object.

CheckdbmssArguments

Checks the arguments of a function of the package dbmss

Converts data to class wmppp

Estimation of the g function

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

spatstat generic functions

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

Estimation of the global confidence interval of simulations

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

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

Estimation of the K function

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

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

Estimation of the Kd function

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

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

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

Estimation of the L function

Test of a point pattern against Complete Spatial Randomness

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

Estimation of the Kmm function

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

Estimation of the inhomogenous K function

Estimation of the Lmm function

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

rPopulationIndependenceM

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

rPopulationIndependenceK

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

Estimation of the m function

parallelCountNbd

Auxiliary functions to count point neighbors

Paracou field station plot 16, partial map

summary.dbmssEnvelope

Summary of a confidence envelope

Class of Weighted, Marked, Planar Point Patterns

Create a Weighted, Marked, Planar Point Pattern

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