TY - DATA
T1 - Supplementary Materials: When is variable importance estimation in species distribution modelling affected by spatial correlation?
PY - 2021/11/26
AU - Nivedita Varma Harisena
AU - Thomas Groen
AU - Albertus G. Toxopeus
AU - Babak Naimi
UR - https://data.4tu.nl/articles/software/Supplementary_Materials_When_is_variable_importance_estimation_in_species_distribution_modelling_affected_by_spatial_correlation_/16752223/1
DO - 10.4121/16752223.v1
KW - Spatial Autocorrelation
KW - Species distribution modelling
KW - sdm
KW - niche models
KW - r code
KW - simulated data
KW - simulated landscapes
KW - variable importance
KW - empirical modelling
KW - spatial data
N2 - <p><b><u>Code and Data
Metadata for Variable importance graphs using simulated variables</u></b></p>

<p>This data entry contains the code and data generated for creating the variable importance
graphs as published in the article: </p>

<p><i>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</i></p>

<p><u>Contents</u></p>

<p>1. A Readme.docx
file</p>

<p>2. Main_script.R
file; Includes the code to be run and the instructions for running the same </p>

<p>3. Functions.R file;
Includes all the functions to be loaded in R before running the Main_script.R
file</p>

<p>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.</p><p>A CODECHECK certificate is available confirming that the computations underlying this article could be independently executed: https://doi.org/10.5281/zenodo.5574909<br><br></p>
ER -