Fisher's information measures and truncated normal distributions (II)

Authors

  • Ion Mihoc “Babes-Bolyai” University, Cluj-Napoca, Romania
  • Cristina Ioana Fătu “Dimitrie Cantemir” University, Cluj-Napoca, Romania

DOI:

https://doi.org/10.33993/jnaat322-746

Keywords:

Fisher information, truncated distribution
Abstract views: 249

Abstract

The aim of this paper is to give some properties for the Fisher information measure when a random variable \(X\) follows a truncated probability distribution. A truncated probability distribution can be regarded as a conditional probability distribution, in the sense that if \(X\) has an unrestricted distribution with the probability density function \(f(x), \) then \(f_{a\leftrightarrow b}(x)\) is the probability density function which governs the behavior of \(X\), subject to the condition that \(X\) is known to lie in \([a,b]\).

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References

Kullback, S., Information Theory and Statistics, Wiley, New York, 1959.

Mihoc, I. and Fătu, C. I., Fisher's Information Measures for the Truncated Normal Distribution (I), Analysis, Functional Equations, Approximation and Convexity, Proceedings of the Conference Held in Honour Professor E. Popoviciu on the Occasion of her 75-th Birthday, Cluj-Napoca, October 15-16, 1999, Editura Carpatica, pp. 171-182, 1999.

Rao, C. R., Liniar Statistical Inference and Its Applications, John Wiley and Sons, Inc., New York, 1965.

Rényi, A., Some fundamental questions of information theory, MTA III, Oszt. Közl., 10, pp. 251-282, 1960.

Rényi, A., Probability Theory, Akadémiai Kiado, Budapest, 1970.

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Published

2003-08-01

How to Cite

Mihoc, I., & Fătu, C. I. (2003). Fisher’s information measures and truncated normal distributions (II). Rev. Anal. Numér. Théor. Approx., 32(2), 177–186. https://doi.org/10.33993/jnaat322-746

Issue

Vol. 32 No. 2 (2003)

Section

Articles

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Copyright (c) 2015 Journal of Numerical Analysis and Approximation Theory

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