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Application of the Poisson process model for the early detection of enterprises' bankruptcy
Author(s) -
Rasson J. P.,
Bertholet V.
Publication year - 1999
Publication title -
applied stochastic models in business and industry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.413
H-Index - 40
eISSN - 1526-4025
pISSN - 1524-1904
DOI - 10.1002/(sici)1526-4025(199910/12)15:4<443::aid-asmb407>3.0.co;2-g
Subject(s) - kernel density estimation , bankruptcy , kernel (algebra) , computer science , parametric statistics , quadratic equation , poisson distribution , linear discriminant analysis , econometrics , process (computing) , poisson process , parametric model , poisson regression , artificial intelligence , mathematics , statistics , economics , finance , population , geometry , demography , combinatorics , estimator , sociology , operating system
This paper describes the construction of a tool with a view to selecting significant variables to detect enterprises' bankruptcy. Based on the Poisson process model, it uses a non‐parametric step forward procedure to estimate densities and produce a discriminant analysis method. An important part of our work is the adaptation of the kernel density estimation to the structure of the enterprises' data. We describe also the results of comparison experiments with classical methods (linear and quadratic as well as the k ‐nearest neighbour). Copyright © 1999 John Wiley & Sons, Ltd.