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Applied asymptotics : = case studies in small-sample statistics /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Applied asymptotics :/ A.R. Brazzale, A.C. Davison, N. Reid.
Reminder of title:
case studies in small-sample statistics /
Author:
Brazzale, A. R.
other author:
Davison, A. C.
Description:
1 online resource (viii, 236 pages) :digital, PDF file(s). :
Notes:
Title from publisher's bibliographic system (viewed on 05 Oct 2015).
Subject:
Statistical hypothesis testing - Asymptotic theory. -
Online resource:
https://doi.org/10.1017/CBO9780511611131
ISBN:
9780511611131 (ebook)
Applied asymptotics : = case studies in small-sample statistics /
Brazzale, A. R.
Applied asymptotics :
case studies in small-sample statistics /A.R. Brazzale, A.C. Davison, N. Reid. - 1 online resource (viii, 236 pages) :digital, PDF file(s). - Cambridge series on statistical and probabilistic mathematics ;23. - Cambridge series on statistical and probabilistic mathematics ;32..
Title from publisher's bibliographic system (viewed on 05 Oct 2015).
In fields such as biology, medical sciences, sociology, and economics researchers often face the situation where the number of available observations, or the amount of available information, is sufficiently small that approximations based on the normal distribution may be unreliable. Theoretical work over the last quarter-century has led to new likelihood-based methods that lead to very accurate approximations in finite samples, but this work has had limited impact on statistical practice. This book illustrates by means of realistic examples and case studies how to use the new theory, and investigates how and when it makes a difference to the resulting inference. The treatment is oriented towards practice and comes with code in the R language (available from the web) which enables the methods to be applied in a range of situations of interest to practitioners. The analysis includes some comparisons of higher order likelihood inference with bootstrap or Bayesian methods.
ISBN: 9780511611131 (ebook)Subjects--Topical Terms:
1141731
Statistical hypothesis testing
--Asymptotic theory.
LC Class. No.: QA277 / .B73 2007
Dewey Class. No.: 519.6
Applied asymptotics : = case studies in small-sample statistics /
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In fields such as biology, medical sciences, sociology, and economics researchers often face the situation where the number of available observations, or the amount of available information, is sufficiently small that approximations based on the normal distribution may be unreliable. Theoretical work over the last quarter-century has led to new likelihood-based methods that lead to very accurate approximations in finite samples, but this work has had limited impact on statistical practice. This book illustrates by means of realistic examples and case studies how to use the new theory, and investigates how and when it makes a difference to the resulting inference. The treatment is oriented towards practice and comes with code in the R language (available from the web) which enables the methods to be applied in a range of situations of interest to practitioners. The analysis includes some comparisons of higher order likelihood inference with bootstrap or Bayesian methods.
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https://doi.org/10.1017/CBO9780511611131
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