rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Essential Statistical Inference
    sub title: Theory and Methods
  name:
    name part: Boos, Dennis D.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Stefanski, L. A.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxu
    date issued: 2013
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XVII, 568 p. 34 illus. online resource.
  abstract: This book is for students and researchers who have had a first year graduate level mathematical statistics course. It covers classical likelihood, Bayesian, and permutation inference; an introduction to basic asymptotic distribution theory; and modern topics like M-estimation, the jackknife, and the bootstrap. R code is woven throughout the text, and there are a large number of examples and problems. An important goal has been to make the topics accessible to a wide audience, with little overt reliance on measure theory. A typical semester course consists of Chapters 1-6 (likelihood-based estimation and testing, Bayesian inference, basic asymptotic results) plus selections from M-estimation and related testing and resampling methodology. Dennis Boos and Len Stefanski are professors in the Department of Statistics at North Carolina State. Their research has been eclectic, often with a robustness angle, although Stefanski is also known for research concentrated on measurement error, including a co-authored book on non-linear measurement error models. In recent years the authors have jointly worked on variable selection methods. .
  table of contents: Roles of Modeling in Statistical Inference.- Likelihood Construction and Estimation.- Likelihood-Based Tests and Confidence Regions.- Bayesian Inference.- Large Sample Theory: The Basics.- Large Sample Results for Likelihood-Based Methods.- M-Estimation (Estimating Equations).- Hypothesis Tests under Misspecification and Relaxed Assumptions .- Monte Carlo Simulation Studies .- Jackknife.- Bootstrap.- Permutation and Rank Tests.- Appendix: Derivative Notation and Formulas.- References.- Author Index.- Example Index -- R-code Index -- Subject Index.
  note: by Dennis D Boos, L. A Stefanski.
  subject:
    topic: Statistics
  subject:
    topic: Statistics
  subject:
    topic: Statistical Theory and Methods
  subject:
    topic: Statistics, general
  subject:
    topic: Statistics and Computing/Statistics Programs
  classification: QA276-280
  classification: 519.5
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Springer Texts in Statistics, 120
  identifier: 9781461448181
  identifier: http://dx.doi.org/10.1007/978-1-4614-4818-1
  record info:
    record creation date: 130217
    record change date: 20151103125431.0
    record identifier: 978-1-4614-4818-1