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DESCRIPTION
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Package: fdacluster
Title: Joint Clustering and Alignment of Functional Data
Version: 0.4.1.9000
Authors@R: c(
person(given = "Aymeric",
family = "Stamm",
role = c("aut", "cre"),
email = "[email protected]",
comment = c(ORCID = "0000-0002-8725-3654")),
person(given = "Laura",
family = "Sangalli",
role = "ctb",
email = "[email protected]"),
person(given = "Piercesare",
family = "Secchi",
role = "ctb",
email = "[email protected]"),
person(given = "Simone",
family = "Vantini",
role = "ctb",
email = "[email protected]"),
person(given = "Valeria",
family = "Vitelli",
role = "ctb",
email = "[email protected]"),
person(given = "Alessandro",
family = "Zito",
role = "ctb",
email = "[email protected]"))
Description: Implementations of the k-means, hierarchical agglomerative and
DBSCAN clustering methods for functional data which allows for jointly
aligning and clustering curves. It supports functional data defined on
one-dimensional domains but possibly evaluating in multivariate codomains.
It supports functional data defined in arrays but also via the 'fd' and
'funData' classes for functional data defined in the 'fda' and 'funData'
packages respectively. It currently supports shift, dilation and affine
warping functions for functional data defined on the real line and uses the
SRVF framework to handle boundary-preserving warping for functional data
defined on a specific interval. Main reference for the k-means algorithm:
Sangalli L.M., Secchi P., Vantini S., Vitelli V. (2010) "k-mean alignment
for curve clustering" <doi:10.1016/j.csda.2009.12.008>. Main reference for
the SRVF framework: Tucker, J. D., Wu, W., & Srivastava, A. (2013)
"Generative models for functional data using phase and amplitude separation"
<doi:10.1016/j.csda.2012.12.001>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
LazyDataCompression: xz
LinkingTo:
Rcpp,
RcppArmadillo,
nloptr
RoxygenNote: 7.3.2
Roxygen: list(markdown = TRUE)
Suggests:
fda,
funData,
future,
knitr,
rmarkdown,
testthat (>= 3.0.0),
withr
Imports:
cli,
cluster,
dbscan,
fdasrvf,
future.apply,
ggplot2,
lpSolve,
nloptr,
progressr,
Rcpp,
rlang,
tibble
Depends:
R (>= 3.5.0)
URL: https://astamm.github.io/fdacluster/, https://github.com/astamm/fdacluster
Config/testthat/edition: 3
VignetteBuilder: knitr