COMPSTAT 2014 Proceedings

Using Storm for scaleable sequential statistical inference

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Abstract

This article describes Storm, an environment for doing streaming data analysis. Two examples of sequential data analysis — computation of a running summary statistic and sequential updating of a posterior distribution — are implemented and their performance is investigated.

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Citation Information

Please cite this proceedings paper as:

Wilson, S. P., Mai, T., Cogan, P., Bhattacharya, A., Robles-Sánchez, O., Aslett, L. J. M., Ó Ríordáin, S. and Roetzer, G. (2014), Using Storm for scaleable sequential statistical inference, in ‘COMPSTAT 2014 Proceedings’.

BibTeX:

@inproceedings{Wilson2014,
  title={Using Storm for scaleable sequential statistical inference},
  author={Wilson, S. P. and Mai, T. and Cogan, P. and Bhattacharya, A. and Robles-S\'{a}nchez, O. and Aslett, L. J. M. and \'{O} R\'{i}ord\'{a}in, S. and Roetzer, G.},
  year={2014},
  booktitle={COMPSTAT 2014 Proceedings}
}

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