Detail výsledku

Statistical Inference of Doubly Left-Censored Samples from Weibull Distribution

FUSEK, M.; MICHÁLEK, J. Statistical Inference of Doubly Left-Censored Samples from Weibull Distribution. In XX International Conference PDMU-2012 Problems of Decision Making under Uncertainties Proceedings - Applied Papers. Brno: Publishing office of the University of Defence, 2012. p. 31-40. ISBN: 978-80-7231-897-1.
Typ
článek ve sborníku konference
Jazyk
anglicky
Autoři
Fusek Michal, Ing., Ph.D., ÚM (FSI)
Michálek Jaroslav, doc. RNDr., CSc., FSI (FSI), ÚM OSO (FSI)
Abstrakt

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.

Klíčová slova

doubly left-censored, Weibull distribution, Fisher information, Type I censoring, maximum likelihood estimator

Rok
2012
Strany
31–40
Sborník
XX International Conference PDMU-2012 Problems of Decision Making under Uncertainties Proceedings - Applied Papers
Konference
Problems of Decision Making under Uncertainties PDMU 2012
ISBN
978-80-7231-897-1
Vydavatel
Publishing office of the University of Defence
Místo
Brno
BibTeX
@inproceedings{BUT95762,
  author="Michal {Fusek} and Jaroslav {Michálek}",
  title="Statistical Inference of Doubly Left-Censored Samples from Weibull Distribution",
  booktitle="XX International Conference PDMU-2012 Problems of Decision Making under Uncertainties Proceedings - Applied Papers",
  year="2012",
  pages="31--40",
  publisher="Publishing office of the University of Defence",
  address="Brno",
  isbn="978-80-7231-897-1"
}
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