126,71 €
140,79 €
-10% with code: EXTRA
Robust Procedures for Estimating and Testing in the Framework of Divergence Measures
Robust Procedures for Estimating and Testing in the Framework of Divergence Measures
126,71
140,79 €
  • We will send in 10–14 business days.
The scope of the contributions to this book will be to present new and original research papers based on MPHIE, MHD, and MDPDE, as well as test statistics based on these estimators from a theoretical and applied point of view in different statistical problems with special emphasis on robustness. Manuscripts given solutions to different statistical problems as model selection criteria based on divergence measures or in statistics for high-dimensional data with divergence measures as loss functio…
  • Publisher:
  • Year: 2021
  • Pages: 334
  • ISBN-10: 3036514600
  • ISBN-13: 9783036514604
  • Format: 17 x 24.4 x 2.7 cm, hardcover
  • Language: English
  • SAVE -10% with code: EXTRA

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The scope of the contributions to this book will be to present new and original research papers based on MPHIE, MHD, and MDPDE, as well as test statistics based on these estimators from a theoretical and applied point of view in different statistical problems with special emphasis on robustness. Manuscripts given solutions to different statistical problems as model selection criteria based on divergence measures or in statistics for high-dimensional data with divergence measures as loss function are considered. Reviews making emphasis in the most recent state-of-the art in relation to the solution of statistical problems base on divergence measures are also presented.

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  • Publisher:
  • Year: 2021
  • Pages: 334
  • ISBN-10: 3036514600
  • ISBN-13: 9783036514604
  • Format: 17 x 24.4 x 2.7 cm, hardcover
  • Language: English English

The scope of the contributions to this book will be to present new and original research papers based on MPHIE, MHD, and MDPDE, as well as test statistics based on these estimators from a theoretical and applied point of view in different statistical problems with special emphasis on robustness. Manuscripts given solutions to different statistical problems as model selection criteria based on divergence measures or in statistics for high-dimensional data with divergence measures as loss function are considered. Reviews making emphasis in the most recent state-of-the art in relation to the solution of statistical problems base on divergence measures are also presented.

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