Open Edouard-Legoupil opened 6 years ago
The objective is to include basic mapping of the variable
to indicate whether the variable should be mapped as:
2 options for the join between the dataset and the polygons:
Maps will have to be faceted using as many facet as modalities within the variable.
As a lot of map will be created, it would make sense to compute l-morand index to help identifying the most meaningful ones. Some references below:
http://rspatial.org/analysis/rst/3-spauto.html https://stats.idre.ucla.edu/r/faq/how-can-i-calculate-morans-i-in-r/ http://www.bias-project.org.uk/ASDARcourse/unit6_slides.pdf https://mgimond.github.io/Spatial/spatial-autocorrelation-in-r.html https://s3.amazonaws.com/geoda/docs/LA_multivariateGeary1.pdf http://www.econ.uiuc.edu/~lab/workshop/Spatial_in_R.html#testing-for-spatial-autocorrelation
Started building some raw map output from data + dictionary: https://github.com/unhcr/koboloadeR/blob/master/R/kobo_map_cat.R https://github.com/unhcr/koboloadeR/blob/master/R/kobo_map_int.R
This should be included in the report generation scripts