Descriptive statistics of non-uniform interval symbolic data

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Descriptive statistics of non-uniform interval symbolic data

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ACM/SIGEVO Summit on Genetic and Evolutionary Computation archive
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation table of contents

Shanghai, China

POSTER SESSION: Poster sessions table of contents

Pages 831-834

Year of Publication: 2009

ISBN:978-1-60558-326-6

Authors

Jun-peng Guo	School of Management, Tianjin University, Tianjin, China
Wen-hua Li	School of Management, Tianjin University, Tianjin, China
Feng Gao	School of Management, Tianjin University, Tianjin, China

Sponsors

SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation
ACM: Association for Computing Machinery

Publisher

ACM New York, NY, USA

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ABSTRACT

As a new kind of data mining method, symbolic data analysis (SDA) can not only decrease the computational complexity of huge data, but also master the property of the sample integrally by data package technology. Interval number is one of the most important types of symbolic data. Previous studies assumed each individual to be uniformly distributed within the interval, but the fact is not so. Non-uniform interval symbolic data is defined in this paper, and the study is concentrated on their descriptive univariate statistics and bivariate statistics. On the basis of the study on empirical distribution function for non-uniform interval symbolic data, the calculation formula of mean and variance of non-uniform interval variables is achieved. Furthermore, covariance and correlation coefficient between two non-uniform interval variables are solved based on their empirical joint distribution function. Finally an example is given.

REFERENCES

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