Publication detail

Statistical Methods for Analyzing Musk Compounds Concentration based on Doubly Left-Censored Samples

FUSEK, M. MICHÁLEK, J.

Original Title

Statistical Methods for Analyzing Musk Compounds Concentration based on Doubly Left-Censored Samples

Type

journal article - other

Language

English

Original Abstract

This contribution is focused on statistical methods for analyzing the worldwide commonly used synthetic musk compounds. Method of maximum likelihood considering doubly left-censored samples is used for statistical modeling of musk compound concentration. As for model distributions, the exponential and Weibull distributions are considered. The suitability of replacement of Weibull distribution with exponential distribution is explored using the asymptotic tests (Lagrange multiplier test, likelihood ratio test, Wald test). Moreover, using the asymptotic properties of maximum likelihood estimates, methods for comparison of two censored samples from exponential distribution are proposed and applied in analysis of concentrations of musk compounds extracted from the fish samples caught in front of and behind a wastewater treatment plant. The power functions of particular tests are compared by simulations.

Keywords

Musk compounds, maximum likelihood, doubly left-censored sample, Weibull distribution, exponential distribution, Lagrange multiplier, likelihood ratio, Wald test

Authors

FUSEK, M.; MICHÁLEK, J.

RIV year

2013

Released

25. 10. 2013

ISBN

1998-0140

Periodical

INTERNATIONAL JOURNAL of MATHEMATICAL MODELS AND METHODS IN APPLIED SCIENCES

Year of study

7

Number

8

State

United States of America

Pages from

755

Pages to

763

Pages count

9

BibTex

@article{BUT102153,
  author="Michal {Fusek} and Jaroslav {Michálek}",
  title="Statistical Methods for Analyzing Musk Compounds Concentration based on Doubly Left-Censored Samples",
  journal="INTERNATIONAL JOURNAL of MATHEMATICAL MODELS AND METHODS IN APPLIED SCIENCES",
  year="2013",
  volume="7",
  number="8",
  pages="755--763",
  issn="1998-0140"
}