An R library for Global Envelope Tests
You can install the
GET library from github through
remotes package with the following two R commands:
If you do not have the R library
remotes installed, install it first by
After installation, in order to start using
GET, load it to R and see
the main help page, which describes the usage of the functions of the library:
In order to use the function random_labelling, the R library
needed. It is available at https://github.com/myllym/marksummary.
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.
spptest has become
GET, which is developed further.
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
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)
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
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