Leisch, Fabian Scheipl, Bjoern Bornkamp, Torsten Hothorn

Fabian Scheipl, Bjoern Bornkamp, Torsten Hothorn

Fabian Scheipl, Bjoern Bornkamp, Martin Maechler, Torsten Hothorn

Authors@R: c(person("Alan", "Genz", role = "aut"),
person("Tetsuhisa", "Miwa", role = "aut"),
person("Friedrich", "Leisch", role = "ctb"),
person("Bjoern", "Bornkamp", role = "ctb"),

person("Bjoern", "Bornkamp", role = "ctb", comment = c(ORCID = "0000-0002-6294-8185")),

person("Martin", "Maechler", role = "ctb", comment = c(ORCID = "0000-0002-8685-9910")),

Title: Multivariate Normal and T Distribution functions of (Dunnett,
Author: Duane Currie <duane.currie@acadiau.ca> and Jianan Peng, using
Description: Computes multivariate student and multivariate normal
integrals, given a correlation matrix structure defined by a
vector bpd, s.t.  rho(i,j) = bpd(i) * bpd(j) (product
Packaged: Thu Jun 15 11:32:36 2006; dcurrie

Description: A function for plotting multivariate time series data

Imports: splines, graphics, grDevices, stats, RColorBrewer
Description: A function for plotting multivariate time series data.

Depends: R (>= 2.13.0), methods, splines, RColorBrewer

Imports: methods, MASS, rTensor, nnTensor, ccTensor, ica, igraph
Description: For single tensor data, any matrix factorization method can be specified the matricised tensor in each dimension by Multi-way Component Analysis (MWCA). An originally extended MWCA is also implemented to specify and decompose multiple matrices and tensors simultaneously (CoupledMWCA). See the reference section of GitHub README.md <https://github.com/rikenbit/mwTensor>, for details of the methods.

Imports: methods, MASS, rTensor, nnTensor, ccTensor, iTensor, igraph
Packaged: 2022-06-15 01:21:21 UTC; tsuyusakikouki

Title: MWA package for causal inference in spatiotemporal event data
Author: Sebastian Schutte and Karsten Donnay
Description: MWA grants insights into causal relationships in spatiotemporal event data.

Title: Causal Inference in Spatiotemporal Event Data
Description: Matched Wake Analysis (mwa) grants insights into causal relationships in spatiotemporal event data.