Site Tools


This is an old revision of the document!

Statistics, econometrics and classification

  1. J. Liu, S. Sriboonchitta, A. Wiboonpongse and T. Denoeux.A trivariate Gaussian copula stochastic frontier model with sample selection. International Journal of Approximate Reasoning (to appear). pdf
  2. S. Sriboonchitta, J. Liu, A. Wiboonpongse and T. Denoeux. A double-copula stochastic frontier model with dependent error components and correction for sample selection. International Journal of Approximate Reasoning, Volume 80, January 2017, Pages 174-184. pdf
  3. A. Wiboonpongse, J. Liu, S. Sriboonchitta and T. Denoeux. Modeling dependence between error components of the stochastic frontier model using copula: Application to Intercrop Coffee Production in Northern Thailand. International Journal of Approximate Reasoning, Vol. 65, Pages 34-44, 2015. pdf
  4. E. Côme, L. Oukhellou, T. Denoeux and P. Aknin. Fault diagnosis of a railway device using semi-supervised independent factor analysis with mixing constraints. Pattern Analysis and Applications, Vol. 15, Number 3, pages 313-326, 2012. pdf
  5. Z. Younes, F. Abdallah, T. Denoeux and H. Snoussi. A dependent multi-label classification method derived from the k-nearest neighbor rule. EURASIP Journal on Advances in Signal Processing, vol. 2011, Article ID 645964, 14 pages, 2011. doi:10.1155/2011/645964. pdf
  6. T. Denoeux and G. Govaert. Un algorithme de classification automatique non paramétrique. Comptes-Rendus de l'Académie des Sciences , t. 324, Série I, p. 673-678, 1997. pdf

User Tools