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-distance and classification problem by Bayesian method

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  • Tai Vovan

Abstract

In this article we suggest a definition for the notion of L1-distance that combines probability density functions and prior probabilities. We also obtain the upper and lower bounds for this distance as well as its relation to other measures. Besides, the relationship between the proposed distance and quantities involved in classification problem by Bayesian method will be established. In practice, calculations are performed by Matlab procedures. As an illustration for applications of the obtained results, the article gives here an estimation for the ability to repay bank debt of some companies in Can Tho City, Vietnam.

Suggested Citation

  • Tai Vovan, 2017. "-distance and classification problem by Bayesian method," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(3), pages 385-401, February.
    • Handle: RePEc:taf:japsta:v:44:y:2017:i:3:p:385-401
    DOI: 10.1080/02664763.2016.1174194
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    Cited by:

    1. Tai Vovan & Dinh Phamtoan & Le Hoang Tuan & Thao Nguyentrang, 2021. "An automatic clustering for interval data using the genetic algorithm," Annals of Operations Research, Springer, vol. 303(1), pages 359-380, August.

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