• Corpus ID: 235489955

Scalable Econometrics on Big Data -- The Logistic Regression on Spark

@inproceedings{Ouattara2021ScalableEO,
  title={Scalable Econometrics on Big Data -- The Logistic Regression on Spark},
  author={Aurelien Ouattara and Matthieu Bult'e and Wan-Ju Lin and Philipp Scholl and Benedikt Veit and Christos Ziakas and Florian Felice and Julien Virlogeux and George N. Dikos},
  year={2021}
}
Extra-large datasets are becoming increasingly accessible, and computing tools designed to handle huge amount of data efficiently are democratizing rapidly. However, conventional statistical and econometric tools are still lacking fluency when dealing with such large datasets. This paper dives into econometrics on big datasets, specifically focusing on the logistic regression on Spark. We review the robustness of the functions available in Spark to fit logistic regression and introduce a… 

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