| Name : R-fsMTS
| |
| Version : 0.1.7
| Vendor : obs://build_opensuse_org/devel:languages:R
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| Release : lp153.13.4
| Date : 2024-06-14 12:10:19
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| Group : Development/Libraries/Other
| Source RPM : R-fsMTS-0.1.7-lp153.13.4.src.rpm
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| Size : 2.26 MB
| |
| Packager : (none)
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| Summary : Feature Selection for Multivariate Time Series
|
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\".
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RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
