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Philippe du Jardin

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First Name:Philippe
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Last Name:du Jardin
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RePEc Short-ID:pdu253
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Location: Lille/Paris, France
Homepage: http://www.edhec.edu/
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Handle: RePEc:edi:edhecfr (more details at EDIRC)
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  1. du Jardin, Philippe, 2012. "The influence of variable selection methods on the accuracy of bankruptcy prediction models," MPRA Paper 44383, University Library of Munich, Germany.
  2. du Jardin, Philippe & Séverin, Eric, 2011. "Predicting corporate bankruptcy using a self-organizing map: An empirical study to improve the forecasting horizon of a financial failure model," MPRA Paper 44262, University Library of Munich, Germany.
  3. du Jardin, Philippe & Séverin, Eric, 2011. "Dividend policy," MPRA Paper 44382, University Library of Munich, Germany.
  4. du Jardin, Philippe & Severin, Eric, 2011. "Forecasting financial failure using a Kohonen map: A comparative study to improve model stability over time," MPRA Paper 39935, University Library of Munich, Germany, revised 03 Apr 2012.
  5. du Jardin, Philippe, 2010. "Predicting bankruptcy using neural networks and other classification methods: the influence of variable selection techniques on model accuracy," MPRA Paper 44375, University Library of Munich, Germany.
  6. du Jardin, Philippe & Séverin, Eric, 2010. "Dynamic analysis of the business failure process: A study of bankruptcy trajectories," MPRA Paper 44379, University Library of Munich, Germany.
  7. du Jardin, Philippe, 2009. "Bankruptcy prediction models: How to choose the most relevant variables?," MPRA Paper 44380, University Library of Munich, Germany.
  8. du Jardin, Philippe, 2008. "Bankruptcy prediction and neural networks: The contribution of variable selection methods," MPRA Paper 44384, University Library of Munich, Germany.
  1. du Jardin, Philippe, 2015. "Bankruptcy prediction using terminal failure processes," European Journal of Operational Research, Elsevier, vol. 242(1), pages 286-303.
  2. du Jardin, Philippe & Séverin, Eric, 2012. "Forecasting financial failure using a Kohonen map: A comparative study to improve model stability over time," European Journal of Operational Research, Elsevier, vol. 221(2), pages 378-396.

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