Книга Empirical Likelihood Methods in Biomedicine and Health

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Empirical Likelihood Methods in Biomedicine and Health provides a compendium of nonparametric likelihood statistical techniques in the perspective of health research applications. It includes detailed descriptions of the theoretical underpinnings of recently developed empirical likelihood-based methods. The emphasis throughout is on the application of the methods to the health sciences, with worked examples using real data.

  • Provides a systematic overview of novel empirical likelihood techniques.
  • Presents a good balance of theory, methods, and applications.
  • Features detailed worked examples to illustrate the application of the methods.
  • Includes R code for implementation.

The book material is attractive and easily understandable to scientists who are new to the research area and may attract statisticians interested in learning more about advanced nonparametric topics including various modern empirical likelihood methods. The book can be used by graduate students majoring in biostatistics, or in a related field, particularly for those who are interested in nonparametric methods with direct applications in Biomedicine.

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20238973
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Язык
Английский
Описание книги

Empirical Likelihood Methods in Biomedicine and Health provides a compendium of nonparametric likelihood statistical techniques in the perspective of health research applications. It includes detailed descriptions of the theoretical underpinnings of recently developed empirical likelihood-based methods. The emphasis throughout is on the application of the methods to the health sciences, with worked examples using real data.

  • Provides a systematic overview of novel empirical likelihood techniques.
  • Presents a good balance of theory, methods, and applications.
  • Features detailed worked examples to illustrate the application of the methods.
  • Includes R code for implementation.

The book material is attractive and easily understandable to scientists who are new to the research area and may attract statisticians interested in learning more about advanced nonparametric topics including various modern empirical likelihood methods. The book can be used by graduate students majoring in biostatistics, or in a related field, particularly for those who are interested in nonparametric methods with direct applications in Biomedicine.

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