Essential statistical inference : theory and methods
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 th...
में बचाया:
| मुख्य लेखकों: | , |
|---|---|
| स्वरूप: | Livre numérique |
| भाषा: | Anglais |
| प्रकाशित: |
New York, NY :
Springer New York
[20..].
Cham : Springer Nature |
| संस्करण: | 1st ed. 2013. |
| श्रृंखला: | Springer Texts in Statistics
120 |
| ऑनलाइन पहुंच: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| टिप्पणी: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Essential statistical inference, theory and methods, Dennis D. Boos, L.A. Stefanski, 2013, New York, Springer, 1 vol. (XVII-568 p.), Springer texts in statistics, 978-1-4614-4817-4 • Essential Statistical Inference, Texte imprimé, 9781489987938 • Essential statistical inference, theory and methods, Dennis D. Boos, L.A. Stefanski, 2013, New York, Springer, 1 vol. (XVII-568 p.), Springer texts in statistics, 978-1-4614-4817-4 • Essential Statistical Inference, Texte imprimé, 9781461448198 |
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| 100 | 1 | |a Boos, Dennis D., |d 19..- | |
| 245 | 1 | 0 | |a Essential statistical inference : |b theory and methods |c by Dennis D. Boos, L. A. Stefanski. |
| 250 | |a 1st ed. 2013. | ||
| 260 | |a New York, NY : |b Springer New York. | ||
| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
| 490 | 0 | |a Springer Texts in Statistics |v 120 |x 2197-4136 | |
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 1 | |a 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. | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a 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. | ||
| 700 | 1 | |a Stefanski, Leonard A. |4 aut | |
| 776 | 0 | |0 175059527 |t Essential statistical inference |o theory and methods |f Dennis D. Boos, L.A. Stefanski |d 2013 |c New York |n Springer |p 1 vol. (XVII-568 p.) |s Springer texts in statistics |z 978-1-4614-4817-4 | |
| 776 | 0 | |t Essential Statistical Inference |b Texte imprimé |z 9781489987938 | |
| 776 | 0 | |0 175059527 |t Essential statistical inference |o theory and methods |f Dennis D. Boos, L.A. Stefanski |d 2013 |c New York |n Springer |p 1 vol. (XVII-568 p.) |s Springer texts in statistics |z 978-1-4614-4817-4 | |
| 776 | 0 | |t Essential Statistical Inference |b Texte imprimé |z 9781461448198 | |
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