README.md

In myllym/spptest: Spatial point process testing

spptest is now GET. Get it now at https://github.com/myllym/GET!

spptest

An R library for spatial point pattern testing

spptest provides envelope and deviation tests for spatial point processes. The main motivation for a new package are the scalings for deviation tests and global envelope tests.

Installation

Install the library to R with the following two R commands:

library(devtools)
install_github('myllym/spptest', ref = 'no_fastdepth')

If you do not have the library ´devtools´ installed, install it first by

install.packages("devtools")

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

library(spptest)
help(spptest) # or help(spptest, help="html")

In order to use the function random_labelling, the R library marksummary is needed. It is currently available by request.

Branches

The branch for current public use is called no_fastdepth. It includes all the same features as the master branch. The only difference is that the master branch includes references to functional depth measures provided by the R library fastdepth which is not yet publicly available.

References

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. (Preprint of the article: http://arxiv.org/abs/1306.1028)

Myllymäki, M., Mrkvička, T., Grabarnik, P., Seijo, H. and Hahn, U. (2016). Global envelope tests for spatial processes. Journal of the Royal Statistical Society: Series B (Statistical Methodology). doi: 10.1111/rssb.12172 (Preprint of the article: http://arxiv.org/abs/1307.0239v4)

Mrkvička, T., Myllymäki, M. and Hahn, U. (2016). Multiple Monte Carlo testing, with applications in spatial point processes. Statistics and Computing. doi: 10.1007/s11222-016-9683-9

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. doi: http://dx.doi.org/10.1016/j.spasta.2016.04.005

myllym/spptest documentation built on May 23, 2019, noon