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ttbary (version 0.3-0)

Barycenter Methods for Spatial Point Patterns

Description

Computes a point pattern in R^2 or on a graph that is representative of a collection of many data patterns. The result is an approximate barycenter (also known as Fréchet mean or prototype) based on a transport-transform metric. Possible choices include Optimal SubPattern Assignment (OSPA) and Spike Time metrics. Details can be found in Müller, Schuhmacher and Mateu (2020) .

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Version

Install

install.packages('ttbary')

Monthly Downloads

194

Version

0.3-0

License

GPL (>= 2)

Maintainer

Dominic Schuhmacher

Last Published

August 15th, 2022

Functions in ttbary (0.3-0)

drezner

Run an Improved Version of the Algorithm by Drezner, Mehrez and Wesolowsky for Finding Barycenters Based on Limited Distances
ppdistnet

Compute Distance Between Two Point Patterns on a Network
kmeansbarynet

Compute Pseudo-Barycenter of a List of Point Patterns on a Network
plotmatch

Plot Optimal Matching between Two Point Patterns
kmeansbary

Compute Pseudo-Barycenter of a List of Point Patterns
netsplit

Incorporate Point Patterns into a Network
kmeansbaryweightnet

Compute weighted Pseudo-Barycenter of a List of Point Patterns on a Network
pplist-data

Simulated Point Pattern Lists
ppdist

Compute Distance Between Two Point Patterns
kmeansbaryeps

Compute Pseudo-Barycenter of a List of Point Patterns (with epsilon-relaxation)
sumppdist

Compute Sum of q-th Powers of Distances Between a Point Pattern and a List of Point Patterns
sumppdistnet

Compute Sum of q-th Powers of Distances Between a Point Pattern and a Collection of Point Patterns on a Network