SpaTimeClus: Model-Based Clustering of Spatio-Temporal Data

Mixture model is used to achieve the clustering goal. Each component is itself a mixture model of polynomial autoregressive regressions whose the logistic weights consider the spatial and temporal information.

AuthorCheam A., Marbac M., and McNicholas P.
Date of publication2016-12-21 11:08:44
MaintainerMatthieu Marbac <matthieu.marbac@gmail.com>
LicenseGPL (>= 2)
Version1.0

View on R-Forge

Files

DESCRIPTION
NAMESPACE
R
R/RcppExports.R R/SpaTimeClus.R R/class.R R/summary.R R/tools.R
data
data/airparif.rda
inst
inst/include
inst/include/STCXEM.h
inst/include/STCXEMnonspatial.h
inst/include/STCXEMspatial.h
inst/include/STCdata.h
inst/include/STCmodel.h
inst/include/STCparam.h
inst/include/STCtune.h
man
man/BuildSTCdata.Rd man/STCcriteria-class.Rd man/STCdata-class.Rd man/STCmodel-class.Rd man/STCmodel.Rd man/STCparam-class.Rd man/STCpartitions-class.Rd man/STCresults-class.Rd man/STCtune-class.Rd man/SpaTimeClus-package.Rd man/airparif.Rd man/print-methods.Rd man/spatimeclus.Rd man/summary-methods.Rd
src
src/Makevars
src/Makevars.win
src/RcppExports.cpp
src/STCXEM.cpp
src/STCXEMnonspatial.cpp
src/STCXEMspatial.cpp
src/SpaTimeClus.cpp
Hadoop Online Training by Edureka

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.