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ttbary (version 0.3-1)

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

0.3-1

License

GPL (>= 2)

Maintainer

Dominic Schuhmacher

Last Published

November 16th, 2022

Functions in ttbary (0.3-1)

ppdistnet

Compute Distance Between Two Point Patterns on a Network
kmeansbarynet

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

Simulated Point Pattern Lists
ppdist

Compute Distance Between Two Point Patterns
kmeansbary

Compute Pseudo-Barycenter of a List of Point Patterns
kmeansbaryweightnet

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

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

Plot Optimal Matching between Two Point Patterns
netsplit

Incorporate Point Patterns into a Network
kmeansbaryeps

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

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

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