Description: Provide regularized principal component analysis incorporating smoothness, sparseness and orthogonality of eigenfunctions
by using the alternating direction method of multipliers algorithm (Wang and Huang, 2017, <DOI:10.1080/10618600.2016.1157483>). The
method can be applied to either regularly or irregularly spaced data, including 1D, 2D, and 3D.
Packaged: 2020-01-08 13:54:37 UTC; wen-tingwang

Suggests: knitr, rmarkdown, testthat (>= 2.1.0), dplyr (>= 1.0.3),
gifski, tidyr, fields, scico, plot3D, pracma, RColorBrewer,
Author: Wen-Ting Wang [aut, cre] (<https://orcid.org/0000-0003-3051-7302>),

Authors@R: person("Stamatis", "Kalogirou", email = "stamatis@lctools.science",
Description: Provides a set of spatial accessibility measures from a set of locations
(demand) to another set of locations (supply). It aims, among others,
to support research on spatial accessibility to health care facilities.
Includes the locations and some characteristics of major public hospitals in Greece.

Authors@R: person("Stamatis", "Kalogirou", email = "skalo@hua.gr",
Description: Provides a set of spatial accessibility measures from a set of locations (demand) to another set of locations (supply). It aims, among others, to support research on spatial accessibility to health care facilities.

Title: Blind Source Separation for Multivariate Spatial Data
Description: Blind source separation for multivariate spatial data based on simultaneous/joint diagonalization of local covariance matrices. This package is an implementation of the methods described in Bachoc, Genton, Nordhausen, Ruiz-Gazen and Virta (2020) <doi:10.1093/biomet/asz079>.
Suggests: sf, RandomFields, knitr, rmarkdown
Packaged: 2021-05-07 08:35:49 UTC; cmuehlmann

Imports: Rcpp (>= 1.0.2), JADE, sp, stats
Suggests: sf, RandomFields, knitr, rmarkdown, markdown
Packaged: 2021-07-28 14:35:50 UTC; cmuehlmann

Packaged: 2021-10-05 13:17:39 UTC; cmuehlmann

Description: Blind source separation for multivariate spatial data based on simultaneous/joint diagonalization of (robust) local covariance matrices. This package is an implementation of the methods described in Bachoc, Genton, Nordhausen, Ruiz-Gazen and Virta (2020) <doi:10.1093/biomet/asz079>.
Imports: Rcpp (>= 1.0.2), JADE, sp, stats, SpatialNP, distances,
Suggests: sf, knitr, rmarkdown, markdown, gstat
Packaged: 2022-11-15 13:17:47 UTC; cmuehlmann