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{ "item_title" : "A Graduate Course on Statistical Inference", "item_author" : [" Bing Li", "G. Jogesh Babu "], "item_description" : "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.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/1/49/399/759/1493997599_b.jpg", "price_data" : { "retail_price" : "179.99", "online_price" : "179.99", "our_price" : "179.99", "club_price" : "179.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
A Graduate Course on Statistical Inference|Bing Li

A Graduate Course on Statistical Inference

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Overview

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.

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Details

  • ISBN-13: 9781493997596
  • ISBN-10: 1493997599
  • Publisher: Springer
  • Publish Date: August 2019
  • Dimensions: 9.21 x 6.14 x 0.88 inches
  • Shipping Weight: 1.59 pounds
  • Page Count: 379

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