GET: Global Envelopes

Implementation of global envelopes for a set of general d-dimensional vectors T in various applications. A 100(1-alpha)% global envelope is a band bounded by two vectors such that the probability that T falls outside this envelope in any of the d points is equal to alpha. Global means that the probability is controlled simultaneously for all the d elements of the vectors. The global envelopes can be used for graphical Monte Carlo and permutation tests where the test statistic is a multivariate vector or function (e.g. goodness-of-fit testing for point patterns and random sets, functional analysis of variance, functional general linear model, n-sample test of correspondence of distribution functions), for central regions of functional or multivariate data (e.g. outlier detection, functional boxplot) and for global confidence and prediction bands (e.g. confidence band in polynomial regression, Bayesian posterior prediction). See Myllymäki and Mrkvička (2020) <arXiv:1911.06583>, Myllymäki et al. (2017) <doi:10.1111/rssb.12172>, Mrkvička et al. (2017) <doi:10.1007/s11222-016-9683-9>, Mrkvička et al. (2020) <doi:10.14736/kyb-2020-3-0432>, Mrkvička et al. (2019) <doi:10.1007/s11009-019-09756-y>, Mrkvička et al. (2019) <arXiv:1902.04926>, Mrkvička et al. (2016) <doi:10.1016/j.spasta.2016.04.005>, and Myllymäki et al. (2020) <doi:10.1016/j.spasta.2020.100436>.

Version: 0.2-1
Depends: R (≥ 2.10)
Imports: ggplot2, graphics, gridExtra, methods, parallel, stats, utils, viridisLite
Suggests: gstat, sp, fda, fda.usc, mvtnorm, patchwork, spatstat, testthat, knitr
Published: 2020-12-12
Author: Mari Myllymäki [aut, cre], Tomáš Mrkvička [aut], Pavel Grabarnik [ctb], Ute Hahn [ctb], Mikko Kuronen [ctb], Michael Rost [ctb], Henri Seijo [ctb]
Maintainer: Mari Myllymäki <mari.myllymaki at>
License: GPL-3
NeedsCompilation: no
Citation: GET citation info
Materials: README
CRAN checks: GET results


Reference manual: GET.pdf
Vignettes: GET: Global envelopes in R
GET: Point patterns
Package source: GET_0.2-1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: GET_0.2-1.tgz, r-oldrel: GET_0.2.tgz
Old sources: GET archive

Reverse dependencies:

Reverse imports: ecostats


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