A Graduate Course on Statistical Inference (Springer Texts in Statistics) 1st ed. 2019 Edition-Original PDF
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A Graduate Course on Statistical Inference (Springer Texts in Statistics) 1st ed. 2019 Edition-Original PDF

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By Bing Li(Author), G. Jogesh Babu(Author)

Size : 4.69 MB

This textbook offers an accessible and comprehensive overview of statistical estimation and inference that reflects current trends in statistical research. It draws from three main themes throughout: the finite-sample theory, the asymptotic theory, and Bayesian statistics. The authors have included a chapter on estimating equations as a means to unify a range of useful methodologies, including generalized linear models, generalized estimation equations, quasi-likelihood estimation, and conditional inference. They also utilize a standardized set of assumptions and tools throughout, imposing regular conditions and resulting in a more coherent and cohesive volume. Written for the graduate-level audience, this text can be used in a one-semester or two-semester course.

Product Details

  • Series: Springer Texts in Statistics
  • Hardcover: 379 pages
  • Publisher: Springer; 1st ed. 2019 edition (August 2, 2019)
  • Language: English
  • ISBN-10: 1493997599
  • ISBN-13: 978-1493997596