Some results of classification problem by Bayesian method and application in credit operation

References

• Altman, D. G. (1991). Statistics in medical journals: Development in 1980s. Statistical in Medicine, 10, 1897–1913. doi: 10.1002/sim.4780101206
   PubMed Web of Science ®Google Scholar
• Christopher, M. B. (2006). Pattern recognition and machine learning. New York, NY: Springer.
   Google Scholar
• Cristianini, N., & Shawe, T. J. (2000). An introduction to support vector machines and other kernel-based learning method. London: Cambridge University.
   Google Scholar
• Fisher, R. A. (1936). The statistical utilization of multiple measurements. Annals of Eugenic, 7, 376–386.
   Google Scholar
• Ghosh, A. K. (2006). Classification using kernel density estimates. Technometrics, 48, 120–132. doi: 10.1198/004017005000000391
   Web of Science ®Google Scholar
• Hastie, T., & Tibshirani, R. (1996). Discriminant adaptive nearest neighbor classification. IEEE Transactions on Pattern Analysis and Machine Intelligence, 18(6), 607–616. doi: 10.1109/34.506411
   Web of Science ®Google Scholar
• Inman, H. F., & Bradley, E. L. (1989). The overlapping coefficient as a measure of agreement between probability distribution sand point estimation of the overlap of two normal densities. Communication in Statistics Theory and Methods, 18, 3851–3874. doi: 10.1080/03610928908830127
   Web of Science ®Google Scholar
• James, J. (2001). Interaction effects in logistic regression. London: Sage.
   Google Scholar
• Jan, Y. K., Cheng, C. W, & Shih, Y. H. (2010). Application of logistic regression analysis of home mortgage loan prepayment and default risk. ICIC Express Letters, 2, 325–331.
   Google Scholar
• Marta, E. (2001). Application of Fisher's method to materials that only release water at high temperatures. Portugaliae Etecfochlmlca Acta, 15, 301–311.
   Google Scholar
• Matusita, K. (1967). On the notion of affinity of several distributions and some of its applications. Annals of the Institute of Statistical Mathematics, 19(1), 181–192. doi: 10.1007/BF02911675
   Web of Science ®Google Scholar
• McLachlan, G. J., & Basford, K. E. (1998). Mixture models: Inference and applications to clustering. New York, NY: Marcel Dekker.
   Google Scholar
• Miller, G., Inkret, W. C., Little, T. T., Martz, H. F., & Schillaci, M. E. (2001). Bayesian prior probability distributions for internal dosimetry. Radiation Protection Dosimetry, 94, 347–352. doi: 10.1093/oxfordjournals.rpd.a006509
   Google Scholar
• Nguyentrang, T., & Vovan, T. (2017). Fuzzy clustering of probability density functions. Journal of Applied Statistics, 44(4), 583–601. doi: 10.1080/02664763.2016.1177502
   Web of Science ®Google Scholar
• Nguyen-Trang, T., & Vo-Van, T. (2017). A new approach for determining the prior probabilities in the classification problem by Bayesian method. Advances in Data Analysis and Classification, 11, 629–643. doi: 10.1007/s11634-016-0253-y
   Google Scholar
• Pham-Gia, T., Nhat, N. D., & Phong, N. V. (2015). Statistical classification using the maximum function. Open Journal of Applied Statistics, 5(7), 665–679. doi: 10.4236/ojs.2015.57068
   Google Scholar
• Pham–Gia, T., Turkkan, N., & Tai, V. V. (2008). Statistical discrimination analysis using the maximum function. Communications in Statistics Simulation and Computation, 37, 320–336. doi: 10.1080/03610910701790475
   Web of Science ®Google Scholar
• Tai, V. V. (2017). - distance and classification problem by Bayesian method. Journal of Applied Statistics, 4(3), 385–401.
   Google Scholar
• Tai, V. V., & Pham-Gia, T. (2010). Clustering probability distributions. Journal of Applied Statistics, 37(11), 1891–1910. doi: 10.1080/02664760903186049
   Web of Science ®Google Scholar
• Tai, V. V., Thao, N. T., & Ha, C. N. (2016). The prior probability in classifying two populations by Bayesian method. Applied Mathematics Engineering and Reliability, 6, 35–40. doi: 10.1201/b21348-7
   Google Scholar
• Toussaint, G. T. (1972). Some inequalities between distance measures for feature. IEEE Transactions on Computers, C-21, 409–410. doi: 10.1109/TC.1972.5008991
   Google Scholar
• Webb, A. (2002). Statistical pattern recognition. London: John Wiley & Sons.
   Google Scholar