Package: fsMTS
Type: Package
Title: Feature Selection for Multivariate Time Series
Version: 0.1.7
Authors@R: person("Dmitry", "Pavlyuk", email = "Dmitry.Pavlyuk@tsi.lv",comment = c(ORCID = "0000-0003-3710-9678"), role = c("aut", "cre"))
Description: Implements feature selection routines for multivariate time series (MTS). 
    The list of implemented algorithms includes: 
    own lags (independent MTS components), 
    distance-based (using external structure, e.g. Pfeifer and Deutsch (1980) <doi:10.2307/1268381>),
    cross-correlation (see  Schelter et al. (2006, ISBN:9783527406234)),
    graphical LASSO (see Haworth and Cheng (2014) <https://www.gla.ac.uk/media/Media_401739_smxx.pdf>),
    random forest (see Pavlyuk (2020) "Random Forest Variable Selection for Sparse Vector Autoregressive Models" in Contributions to Statistics, in production),
    least angle regression (see Gelper and Croux (2008) <https://lirias.kuleuven.be/retrieve/16024>), 
    mutual information (see  Schelter et al. (2006, ISBN:9783527406234), Liu et al. (2016) <doi:10.1109/ChiCC.2016.7554480>),
    and partial spectral coherence (see Davis et al.(2016) <doi:10.1080/10618600.2015.1092978>). 
    In addition, the package implements functions for ensemble feature selection (using feature ranking and majority voting).
    The package is implemented within Dmitry Pavlyuk's research project No. 1.1.1.2/VIAA/1/16/112 "Spatiotemporal urban traffic modelling using big data".
License: GPL-3
Depends: R (>= 3.6)
Imports: glasso,lars,mpmi,freqdom,randomForestSRC
Suggests: knitr, rmarkdown, sparsevar, plot.matrix, svMisc, MTS
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.2
Author: Dmitry Pavlyuk [aut, cre] (<https://orcid.org/0000-0003-3710-9678>)
Maintainer: Dmitry Pavlyuk <Dmitry.Pavlyuk@tsi.lv>
Repository: CRAN
Repository/R-Forge/Project: fsmts
Repository/R-Forge/Revision: 24
Repository/R-Forge/DateTimeStamp: 2022-04-25 17:44:07
Date/Publication: 2022-04-26 09:00:07 UTC
NeedsCompilation: no
Packaged: 2022-04-25 17:51:56 UTC; rforge
Built: R 4.1.3; ; 2023-04-17 20:00:24 UTC; windows
