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Description
  • When analyzing environmental or chemical data, we often have to deal with left-censored observations with one or more detection limits. Estimators of the parameters are derived for Type I doubly left-censored data having two detection limits and assuming an underlying Weibull distribution. Maximum likelihood estimators of the parameters are given and examined considering various censoring schemes. The expected Fisher information matrix (FIM) is analytically determined and compared with the sample FIM using simulations. Simulations are focused primarily on the properties of estimates for small sample sizes.
  • When analyzing environmental or chemical data, we often have to deal with left-censored observations with one or more detection limits. Estimators of the parameters are derived for Type I doubly left-censored data having two detection limits and assuming an underlying Weibull distribution. Maximum likelihood estimators of the parameters are given and examined considering various censoring schemes. The expected Fisher information matrix (FIM) is analytically determined and compared with the sample FIM using simulations. Simulations are focused primarily on the properties of estimates for small sample sizes. (en)
Title
  • Statistical Inference of Doubly Left-Censored Samples from Weibull Distribution
  • Statistical Inference of Doubly Left-Censored Samples from Weibull Distribution (en)
skos:prefLabel
  • Statistical Inference of Doubly Left-Censored Samples from Weibull Distribution
  • Statistical Inference of Doubly Left-Censored Samples from Weibull Distribution (en)
skos:notation
  • RIV/00216305:26210/12:PU100986!RIV13-MSM-26210___
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  • 171180
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  • RIV/00216305:26210/12:PU100986
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  • doubly left-censored, Weibull distribution, Fisher information, Type I censoring, maximum likelihood estimator (en)
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  • [E70FE7EA46CA]
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  • Brno
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  • Brno
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  • XX International Conference PDMU-2012 Problems of Decision Making under Uncertainties Proceedings - Applied Papers
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  • Fusek, Michal
  • Michálek, Jaroslav
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number of pages
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  • Publishing office of the University of Defence
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  • 978-80-7231-897-1
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  • 26210
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