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Mathematical Statistics: An Introduction to Likelihood Based Inference – PDF

eBook details

  • Author: Richard J. Rossi
  • File Size: 4 MB
  • Format: PDF
  • Length: 464 pages
  • Publisher: Wiley; 1st edition
  • Publication Date: June 14, 2018
  • Language: English
  • ASIN: B07DS3WLG4
  • ISBN-10: 1118771044
  • ISBN-13: 9781118771044

Original price was: $100.00.Current price is: $12.00.

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About The Author

Richard J. Rossi

Presents a unified method to parametric evaluation, hypothesis screening, self-confidence periods, and analytical modeling, which are distinctively based upon the likelihood function. This ebook, Mathematical Statistics: An Introduction to Likelihood Based Inference (PDF), addresses mathematical data for very first year graduate and upper- undergrads trainees, connecting chapters on evaluation, hypothesis screening, self-confidence periods, and analytical designs together to provide a unifying concentrate on the likelihood function. It likewise highlights the crucial concepts in analytical modeling, such as rapid household circulations, sufficiency, and big sample residential or commercial properties. Rossi’s Mathematical Statistics: An Introduction to Likelihood Based Inference PDF makes sophisticated subjects available and reasonable and covers numerous subjects in more depth than common mathematical data books. It consists of many case research studies, terrific examples, a a great deal of workouts varying from drill and ability to very challenging issues, and a lot of the crucial theorems of mathematical data in addition to their evidence. In addition to the linked chapters discussed above, Mathematical Statistics covers likelihood- based evaluation, with focus on multidimensional criterion areas and variety reliant assistance. It likewise consists of a chapter on self-confidence periods, which includes examples of precise self-confidence periods in addition to the basic big sample self-confidence periods based upon the MLE’s and bootstrap self-confidence periods. There’s likewise a chapter on parametric analytical designs including areas on Poisson regression, non- iid observations, logistic regression, direct regression, and direct designs.

  • Features fine examples, issues, and solutions
  • Includes areas on Bayesian evaluation and reputable periods
  • Prepares university student with the tools required to succeed in their future operate in stats information science
  • Emphasizes the crucial concepts to analytical modeling, such as rapid household circulation, sufficiency, and big sample residential or commercial properties
  • Includes useful case research studies consisting of genuine- life information gathered from the Donner celebration, Yellowstone National Park, and the Titanic trip

Mathematical Statistics: An Introduction to Likelihood Based Inference is a perfect etextbook for graduate and upper- undergraduate courses in mathematical data, possibility, and/or analytical inference.

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