Time-dependent residual Fisher information and distance for some special continuous distributions
Fisher information is a measure to quantify information and have important inferential, scaling and uncertainty properties. Kharazmi and Asadi (Braz. J. Prob. Stat. 32, 795-814, 2018) presented the time-dependent Fisher information of any density function. Specifically, they considered a nonnegative...
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| Published in | Communications in statistics. Simulation and computation Vol. 53; no. 9; pp. 4331 - 4351 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
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Philadelphia
Taylor & Francis
01.09.2024
Taylor & Francis Ltd |
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| ISSN | 0361-0918 1532-4141 |
| DOI | 10.1080/03610918.2022.2146136 |
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| Abstract | Fisher information is a measure to quantify information and have important inferential, scaling and uncertainty properties. Kharazmi and Asadi (Braz. J. Prob. Stat. 32, 795-814, 2018) presented the time-dependent Fisher information of any density function. Specifically, they considered a nonnegative continuous random (lifetime) variable X and define the time-dependent Fisher information and distance for density function of the residual random variable associated to X. In this article, we computed the mentioned measures for generalized gamma, Beta prime, generalized inverse Gaussian and truncated skew-normal densities. For generalized gamma, beta prime and generalized inverse Gaussian densities, exact expressions are provided and, for truncated skew-normal case, we computed the mentioned measures for truncated (at positive support) skew-normal random variables by using exact expressions in terms of cumulants and moments. Some numerical results are illustrated. |
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| AbstractList | Fisher information is a measure to quantify information and have important inferential, scaling and uncertainty properties. Kharazmi and Asadi (Braz. J. Prob. Stat. 32, 795-814, 2018) presented the time-dependent Fisher information of any density function. Specifically, they considered a nonnegative continuous random (lifetime) variable X and define the time-dependent Fisher information and distance for density function of the residual random variable associated to X. In this article, we computed the mentioned measures for generalized gamma, Beta prime, generalized inverse Gaussian and truncated skew-normal densities. For generalized gamma, beta prime and generalized inverse Gaussian densities, exact expressions are provided and, for truncated skew-normal case, we computed the mentioned measures for truncated (at positive support) skew-normal random variables by using exact expressions in terms of cumulants and moments. Some numerical results are illustrated. |
| Author | Kharazmi, Omid Contreras-Reyes, Javier E. Gallardo, Diego I. |
| Author_xml | – sequence: 1 givenname: Javier E. orcidid: 0000-0003-1172-5456 surname: Contreras-Reyes fullname: Contreras-Reyes, Javier E. organization: Instituto de Estadística, Facultad de Ciencias, Universidad de Valparaíso – sequence: 2 givenname: Diego I. surname: Gallardo fullname: Gallardo, Diego I. organization: bDepartamento de Matemática, Facultad de Ingeniería, Universidad de Atacama – sequence: 3 givenname: Omid orcidid: 0000-0003-4176-9708 surname: Kharazmi fullname: Kharazmi, Omid organization: cDepartment of Statistics, Vali-e-Asr University of Rafsanjan |
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| SubjectTerms | Beta prime Computation Continuity (mathematics) Density Fisher information Generalized gamma Generalized inverse Generalized inverse Gaussian Random variables Residual fisher information Time dependence Time measurement Truncated skew-normal |
| Title | Time-dependent residual Fisher information and distance for some special continuous distributions |
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