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SFS
View on CRAN: Click
here
Download and install SFS package within the R console
Install from CRAN:
install.packages("SFS")
Install from Github:
library("remotes")
install_github("cran/SFS") Install by package version:
library("remotes")
install_version("SFS", "0.1.4") Attach the package and use:
library("SFS")
Maintained by
Utz-Uwe Haus
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-06-20
Latest Update: 2019-05-07
Description:
An implementation of the Similarity-First Search algorithm (SFS), a combinatorial algorithm which can be used to solve the seriation problem and to recognize some structured weighted graphs. The SFS algorithm represents a generalization to weighted graphs of the graph search algorithm Lexicographic Breadth-First Search (Lex-BFS), a variant of Breadth-First Search. The SFS algorithm reduces to Lex-BFS when applied to binary matrices (or, equivalently, unweighted graphs). Hence this library can be also considered for Lex-BFS applications such as recognition of graph classes like chordal or unit interval graphs. In fact, the SFS seriation algorithm implemented in this package is a multisweep algorithm, which consists in repeating a finite number of SFS iterations (at most n sweeps for a matrix of size n). If the data matrix has a Robinsonian structure, then the ranking returned by the multistep SFS algorithm is a Robinson ordering of the input matrix. Otherwise the algorithm can be used as a heuristic to return a ranking partially satisfying the Robinson property.
How to cite:
Utz-Uwe Haus (2017). SFS: Similarity-First Search Seriation Algorithm. R package version 0.1.4, https://cran.r-project.org/web/packages/SFS. Accessed 07 Aug. 2026.
Previous versions and publish date:
Other packages that cited SFS R package
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Other R packages that SFS depends,
imports, suggests or enhances
Complete documentation for SFS
Functions, R codes and Examples using
the SFS R package
Some associated functions: SFS_read . SFS_sfs .
Some associated R codes: RcppExports.R . SFS.R . Full SFS package functions and examples
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