Suggests: testthat, covr, pillar (>= 1.0.0), crayon, rmarkdown, knitr,

Suggests: testthat, covr, pillar (>= 1.0.0), tibble (>= 1.1.0), crayon,

rmarkdown, knitr, withr, spelling, vctrs (>= 0.3.0)

Packaged: 2021-12-08 16:14:56 UTC; gaborcsardi

Title: Feature Selection for Multivariate Time Series
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:
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>),
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".
Suggests: knitr, rmarkdown, sparsevar, plot.matrix, svMisc, MTS
Author: Dmitry Pavlyuk [aut, cre] (<https://orcid.org/0000-0003-3710-9678>)

Title: Managing and Visualizing Brain Surface Data
Description: Provides high-level access to 'FreeSurfer' <http://freesurfer.net/> neuroimaging data on the level of subjects and groups. Load morphometry data, surfaces and brain parcellations based on atlases. Mask data using labels, load data for specific atlas regions only, and visualize the results directly in 'R'.
Imports: reshape, reshape2, freesurferformats (>= 0.1.3), pkgfilecache