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- Tanaka Minoru
- Department of Information Sciences, Science University of Tokyo
Bibliographic Information
- Other Title
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- Estimation of the Autocorrelation Coeff
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Abstract
The sequence of positive random variables {Yt} is called a stationary lognormal process with parameters μ, σ2 and ρh, h=0, ±1, ±2, …, if the sequence of logarithmic variables {ln Yt} is stationary and Gaussian with mean μ, variance σ2 and autocorrelation coefficients ρh. This paper deals with the problem of estimating the autocorrelation coefficients of a stationary lognormal process with known μ and σ2. Efficiency of the usual sample autocorrelations relative to a simplified estimate is studied under the assumption that the transformed process is Markovian. The result leads to the choice of the biased simplified estimate as a better estimate than the unbiased sample autocorrelations for small lag h and small σ. Other unbiased estimates are constructed and their variances are evaluated.
Journal
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- Journal of the Japan Statistical Society, Japanese Issue
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Journal of the Japan Statistical Society, Japanese Issue 17 (2), 137-148, 1987
Japan Statistical Society
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Details 詳細情報について
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- CRID
- 1390282679413617792
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- NII Article ID
- 130003582429
- 40002988179
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- NII Book ID
- AA1105098X
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- ISSN
- 21891478
- 03895602
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- MRID
- 930405
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- NDL BIB ID
- 3163973
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- Text Lang
- en
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- Data Source
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- JaLC
- NDL
- CiNii Articles
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- Abstract License Flag
- Disallowed