Clusters longitudinal trajectories over time (can be unequally
spaced, unequal length time series and/or partially overlapping series) on
a common time axis. Performs k-means clustering on a single continuous
variable measured over time, where each mean is defined by a thin plate
spline fit to all points in a cluster. Distance is MSE across trajectory
points to cluster spline. Provides graphs of derived cluster splines,
silhouette plots, and Adjusted Rand Index evaluations of the number
of clusters. Scales well to large data with multicore parallelism available
to speed computation.

Methods for joint dimension reduction and clustering
A collection of methods for joint dimension reduction and
clustering
c(person("Angelos", "Markos", email = "amarkos@gmail.com", role =
c("aut", "cre")), person("Alfonso", "Iodice D' Enza", role = "aut"),
person("Michel", "Van de Velden", role = "aut"))
'MCAk.r' 'disjMake.r' 'fuzzyMCAk.r' 'groupals.r' 'iFCB.r'
'FactorialKM.R' 'ReducedKM.R' 'plotrd.r'
Angelos Markos [aut, cre],
Alfonso Iodice D' Enza [aut],
Michel Van de Velden [aut]

'MCAk.r' 'disjMake.r' 'fuzzyMCAk.r' 'groupals.r' 'iFCB.r'
'FactorialKM.r' 'ReducedKM.r' 'plotrd.r' 'ed.r' 'nrm.r'
'orth.r' 'rosplit.r'

corpcor, e1071, ggplot2, randtoolbox, irlba

Methods for Joint Dimension Reduction and Clustering
A class of methods that combine dimension reduction and clustering of continuous or categorical data. For continuous data, the package contains implementations of factorial K-means (Vichi and Kiers 2001; <DOI:10.1016/S0167-9473(00)00064-5>) and reduced K-means (De Soete and Carroll 1994; <DOI:10.1007/978-3-642-51175-2_24>); both methods that combine principal component analysis with K-means clustering. For categorical data, the package provides MCA K-means (Hwang, Dillon and Takane 2006; <DOI:10.1007/s11336-004-1173-x>), i-FCB (Iodice D'Enza and Palumbo 2013, <DOI:10.1007/s00180-012-0329-x>) and Cluster Correspondence Analysis (van de Velden, Iodice D'Enza and Palumbo 2016; <DOI:10.1007/s11336-016-9514-0>), which combine multiple correspondence analysis with K-means.
Alfonso Iodice D'Enza [aut], Angelos Markos [aut, cre], Michel van de Velden [ctb]
corpcor, ggrepel, GGally, fpc, cluster, dplyr, plyr