Supplementary Materials: When is variable importance estimation in species distribution modelling affected by spatial correlation?
DOI: 10.4121/16752223
Software
Code and Data Metadata for Variable importance graphs using simulated variables
This data entry contains the code and data generated for creating the variable importance graphs as published in the article:
Harisena, N. V., Groen, T. A., Toxopeus, A. G., & Naimi, B. (2021). When is variable importance estimation in species distribution modelling affected by spatial correlation? Ecography, 44(5), 778–788. 10.1111/ecog.05534
Contents
1. A Readme.docx file
2. Main_script.R file; Includes the code to be run and the instructions for running the same
3. Functions.R file; Includes all the functions to be loaded in R before running the Main_script.R file
4. Generated_Data; folder with all .Rdata files for each code step as detailed in Main_script.R along with the output .csv and .jpg files that can be matched with the output images in the publication.
A CODECHECK certificate is available confirming that the computations underlying this article could be independently executed: https://doi.org/10.5281/zenodo.5574909
History
- 2021-11-26 first online, published, posted
Publisher
4TU.ResearchDataFormat
.docx; .R; .Rdata; .zipAssociated peer-reviewed publication
When is variable importance estimation in species distribution modelling affected by spatial correlation?References
Funding
- 4TU.ResearchData FAIR data fund
Organizations
Twente University, Faculty of Geo-Information Science and Earth Observation (ITC)ETH Zürich - IRL
Planning of Landscape and Urban Systems, PLUS
DATA
Files (5)
- 14,417 bytesMD5:
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Readme.docx - 30,664 bytesMD5:
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all_functions.R - 1,750,598,859 bytesMD5:
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Generated_data.zip - 8,214 bytesMD5:
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Main_script_with_documentation.R - 218 bytesMD5:
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Script_and_data.Rproj -
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