Update README.md

README.md

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 # Regularized target encoding outperforms traditional methods in supervised machine learning with high cardinality features
 
-This repository contains code and results for the paper "Regularized target encoding outperforms traditional methods in supervised machine learning with high cardinality features".
+This repository contains code and results for the paper "Regularized target encoding outperforms traditional methods in supervised machine learning with high cardinality features" published in the journal Computational Statistics:
+
+Pargent, F., Pfisterer, F., Thomas, J. et al. Regularized target encoding outperforms traditional methods in supervised machine learning with high cardinality features. Comput Stat (2022). https://doi.org/10.1007/s00180-022-01207-6
 
 DESCRIPTION OF FOLDERS AND FILES:
 
@@ -22,4 +24,4 @@ DESCRIPTION OF FOLDERS AND FILES:
 - *supplementary_material.Rmd* builds *supplementary_material.pdf* which contains additional information not included in the manuscript
 - *references.bib* contains all references used in the manuscript
 
-For questions and remarks feel free to contact the manuscript authors.
+For questions and remarks feel free to contact the manuscript authors.