Linear Regression Analysis
Alan J. Lee, George A. F. Seber
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169,99 €
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Naturwissenschaften, Medizin, Informatik, Technik / Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik
Beschreibung
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.
Rezensionen
(Journal of Statistical Computation and Simulation, July
2005)
"With excellent motivating and presenting style, this book is suitable for a beginning graduate level regression course."
"With excellent motivating and presenting style, this book is suitable for a beginning graduate level regression course."
(Zentralblatt Math,
Vol. 1029, 2004)
"...revises and expands the standard text, providing extensive coverage of state-of-the-art theory..."
"...revises and expands the standard text, providing extensive coverage of state-of-the-art theory..."
(Technometrics, Vol. 45, No. 4, November 2003)
"...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..."
"...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..."
(Quarterly of Applied Mathematics, Vol. LXI, No. 3,
September 2003)
"...rewritten to reflect current thinking, such as the major advances in computing during the past 25 years."
"...rewritten to reflect current thinking, such as the major advances in computing during the past 25 years."
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Schlagwörter
Modell (Math.), Applied Probability & Statistics - Models, Angew. Wahrscheinlichkeitsrechn. u. Statistik / Modelle, Regression Analysis, Statistik, Regressionsanalyse, Statistics