jiro74/get

Global Envelopes in R

GET: Global envelopes in R

The R package provides global envelopes which can be used in various situations including detection of central or outlying vectors or functions, functional boxplots, goodness-of-fit testing with multivariate or functional test statistics, functional ANOVA, functional GLM, n-sample correspondence of distribution functions, confidence and prediction bands from a set of multivariate vectors or functions.

Installation

You can install the GET library from github through remotes package with the following two R commands:

library(remotes)
install_github('myllym/GET')

If you do not have the R library remotes installed, install it first by

install.packages("remotes")

After installation, in order to start using GET, load it to R and see the main help page, which describes the functions of the library:

library(GET)
help('GET-package')

Branches

The branch for public use is called master. There are no other public branches at the moment. The branch 'no_fastdepth' of the library spptest was taken as the master branch of GET September 21, 2016. The library spptest has become GET, which is developed further.

References

###To cite GET in publications use:

Myllymäki, M., Mrkvička, T., Grabarnik, P., Seijo, H. and Hahn, U. (2017). Global envelope tests for spatial processes. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 79: 381-404. doi: 10.1111/rssb.12172 http://dx.doi.org/10.1111/rssb.12172 (You can find the preprint of the article here: http://arxiv.org/abs/1307.0239v4)

Mrkvička, T., Myllymäki, M. and Hahn, U. (2017). Multiple Monte Carlo testing, with applications in spatial point processes. Statistics and Computing 27 (5): 1239-1255. https://doi.org/10.1007/s11222-016-9683-9

###If you use functional ANOVA, please also cite:

Mrkvička, T., Hahn, U. and Myllymäki, M. (2016). A one-way ANOVA test for functional data with graphical interpretation. arXiv:1612.03608 [stat.ME] (http://arxiv.org/abs/1612.03608)

###If you use deviation tests, please also cite:

Myllymäki, M., Grabarnik, P., Seijo, H., and Stoyan, D. (2015). Deviation test construction and power comparison for marked spatial point patterns. Spatial Statistics 11: 19-34. https://doi.org/10.1016/j.spasta.2014.11.004 (You can find the preprint of the article here: http://arxiv.org/abs/1306.1028)

###If you use apply tests to spatial residuals, please also cite:

Mrkvička, T., Soubeyrand, S., Myllymäki, M., Grabarnik, P., and Hahn, U. (2016). Monte Carlo testing in spatial statistics, with applications to spatial residuals. Spatial Statistics 18, Part A: 40--53. https://doi.org/10.1016/j.spasta.2016.04.005