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FPDclustering
View on CRAN: Click
here
Download and install FPDclustering package within the R console
Install from CRAN:
install.packages("FPDclustering")
Install from Github:
library("remotes")
install_github("cran/FPDclustering")
Install by package version:
library("remotes")
install_version("FPDclustering", "2.3.5")
Attach the package and use:
library("FPDclustering")
Maintained by
Cristina Tortora
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.FPDclustering . FPDclustering citation info . FPDclustering results . FPDclustering.pdf . FPDclustering_2.3.5.tar.gz . FPDclustering_2.3.5.zip . FPDclustering_2.3.5.zip . FPDclustering_2.3.5.zip . FPDclustering_2.3.5.tgz . FPDclustering_2.3.5.tgz . FPDclustering_2.3.5.tgz . FPDclustering_2.3.5.tgz . FPDclustering_2.3.5.tgz . FPDclustering_2.3.5.tgz . FPDclustering archive . https://CRAN.R-project.org/package=FPDclustering .
First Published: 2014-12-17
Latest Update: 2022-08-31
Description:
Probabilistic distance clustering (PD-clustering) is an iterative, distribution free, probabilistic clustering method. PD-clustering assigns units to a cluster according to their probability of membership, under the constraint that the product of the probability and the distance of each point to any cluster centre is a constant. PD-clustering is a flexible method that can be used with non-spherical clusters, outliers, or noisy data. PDQ is an extension of the algorithm for clusters of different size. GPDC and TPDC uses a dissimilarity measure based on densities. Factor PD-clustering (FPDC) is a factor clustering method that involves a linear transformation of variables and a cluster optimizing the PD-clustering criterion. It works on high dimensional data sets.
How to cite:
Cristina Tortora (2014). FPDclustering: PD-Clustering and Related Methods. R package version 2.3.5, https://cran.r-project.org/web/packages/FPDclustering. Accessed 04 Apr. 2025.
Previous versions and publish date:
1.0 (2014-12-17 01:54), 1.1 (2016-05-18 01:23), 1.2 (2017-08-23 20:09), 1.3.1 (2019-08-22 18:50), 1.3 (2019-04-12 12:03), 1.4.1 (2020-01-28 21:50), 1.4 (2020-01-09 13:30), 2.0 (2021-09-11 08:10), 2.1 (2022-02-02 10:00), 2.2 (2022-08-31 16:00), 2.3.1 (2024-01-30 01:10), 2.3.2 (2024-12-12 17:20), 2.3.3 (2025-01-28 00:30), 2.3.4 (2025-02-13 09:40), 2.3 (2024-01-25 23:20)
Other packages that cited FPDclustering R package
View FPDclustering citation profile
Other R packages that FPDclustering depends,
imports, suggests or enhances
Complete documentation for FPDclustering
Functions, R codes and Examples using
the FPDclustering R package
Some associated functions: FPDC . GPDC . PDC . PDQ . Silh . Star . TPDC . TuckerFactors . ais . asymmetric20 . asymmetric3 . outliers . plot.FPDclustering . summary.FPDclustering .
Some associated R codes: FPDC-internal.R . FPDC.R . GPDC.R . PDC.R . PDQ.R . Silh.R . TPDC.R . TuckerFactors.R . disS.R . Full FPDclustering package functions and examples
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