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Linear Regression Analysis 2nd edition [Kõva köide]

3.92/5 (25 hinnangut Goodreads-ist)
(University of Auckland, New Zealand), (University of Auckland, New Zealand)
  • Formaat: Hardback, 592 pages, kõrgus x laius x paksus: 238x164x38 mm, kaal: 989 g, Charts: 2 B&W, 0 Color; Drawings: 5 B&W, 0 Color; Tables: 21 B&W, 0 Color; Graphs: 18 B&W, 0 Color
  • Sari: Wiley Series in Probability and Statistics
  • Ilmumisaeg: 25-Feb-2003
  • Kirjastus: John Wiley & Sons Inc
  • ISBN-10: 0471415405
  • ISBN-13: 9780471415404
Teised raamatud teemal:
Linear Regression Analysis 2nd editionSuurem pilt
  • Formaat: Hardback, 592 pages, kõrgus x laius x paksus: 238x164x38 mm, kaal: 989 g, Charts: 2 B&W, 0 Color; Drawings: 5 B&W, 0 Color; Tables: 21 B&W, 0 Color; Graphs: 18 B&W, 0 Color
  • Sari: Wiley Series in Probability and Statistics
  • Ilmumisaeg: 25-Feb-2003
  • Kirjastus: John Wiley & Sons Inc
  • ISBN-10: 0471415405
  • ISBN-13: 9780471415404
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780471415404.html
Märksõnad:
Updating and expanding the original text, this new edition covers the current theory and applications of linear regression analysis. It provides a survey of the research literature and outlines the solutions to approximately 200 sample problems. Particular attention is given to diagnostics, model fitting, model selection, and prediction. Seber and Lee have each taught statistics at the University of Auckland. Annotation (c) Book News, Inc., Portland, OR (booknews.com)

Concise, mathematically clear, and comprehensive treatment of the subject.
* Expanded coverage of diagnostics and methods of model fitting.
* Requires no specialized knowledge beyond a good grasp of matrix algebra and some acquaintance with straight-line regression and simple analysis of variance models.
* More than 200 problems throughout the book plus outline solutions for the exercises.
* This revision has been extensively class-tested.

Arvustused

"With excellent motivating and presenting style, this book is suitable for a beginning graduate level regression course." (Journal of Statistical Computation and Simulation, July 2005) "...revises and expands the standard text, providing extensive coverage of state-of-the-art theory..." (Zentralblatt Math, Vol. 1029, 2004)

"...largely rewritten...very useful for self-study...an excellent choice for a course in linear models and researchers who are interested in recent literature in the fields..." (Technometrics, Vol. 45, No. 4, November 2003)

...rewritten to reflect current thinking, such as the major advances in computing during the past 25 years. (Quarterly of Applied Mathematics, Vol. LXI, No. 3, September 2003)

Preface.
Vectors of Random Variables.
Multivariate Normal Distribution.
Linear Regression: Estimation and Distribution Theory.
Hypothesis Testing.
Confidence Intervals and Regions.
Straight-Line Regression.
Polynomial Regression.
Analysis of Variance.
Departures from Underlying Assumptions.
Departures from Assumptions: Diagnosis and Remedies.
Computational Algorithms for Fitting a Regression.
Prediction and Model Selection.
Appendix A. Some Matrix Algebra.
Appendix B. Orthogonal Projections.
Appendix C. Tables.
Outline Solutions to Selected Exercises.
References.
Index.


GEORGE A. F. SEBER, PhD, is Professor Emeritus of Statistics at the University of Auckland, New Zealand. ALAN J. LEE, PhD, is the Chairman of the Department of Statistics at the University of Auckland.