Dynamic Information Volatility Function
Keywords:Shannon entropy, Information volatity, Reliability measures, Stochastic orders, Characterization
Liu (2007) discussed a new measure, known as the information volatility function to study the variability of the uncertainty contained in a probability distribution. In the present paper, we extend this concept to the residual random variable, a dynamic information volatility function and study its usefulness in reliability modelling. Different ageing and characterization properties of dynamic information volatility function are also derived.
J. BEIRLANT, E. J. DUDEWICZ, L. GYÖRFI, E. C. VAN DER MEULEN (1997). Nonparametric entropy estimation: An overview. International Journal of Mathematical and Statistical Sciences, 6, no. 1, pp. 17–39.
N. EBRAHIMI (1996). How to measure uncertainty in the residual life time distribution. Sankhy¯a A, pp. 48–56.
D. E. LAKE (2009). Nonparametric entropy estimation using kernel densities. Methods in Enzymology, 467, pp. 531–546.
J. LIU (2007). Information Theoretic Content and Probability. Ph.D. thesis, University of Florida.
N. U. NAIR, K. K. SUDHEESH (2010). Characterization of continuous distributions by properties of conditional variance. Statistical Methodology, 7, no. 1, pp. 30–40.
M. RAO, Y. CHEN, B. C. VEMURI, F. WANG (2004). Cumulative residual entropy: A new measure of information. IEEE Transactions on Information Theory, 50, no. 6, pp. 1220–1228.
P. G. SANKARAN, R. P. GUPTA (1999). Characterization of lifetime distributions using measure of uncertainty. Calcutta Statistical Association Bulletin, 49, no. 3-4, pp. 159–166.
C. E. SHANNON (1948). A mathematical theory of communication. Bell System Technical Journal, 27, no. 3, pp. 379–423.
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