Produktbild: Linear Model Theory

Linear Model Theory With Examples and Exercises

Fr. 191.00

inkl. gesetzl. MwSt., Versandkostenfrei


Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

03.11.2020

Verlag

Springer

Seitenzahl

504

Maße (L/B/H)

24.1/16/3.4 cm

Gewicht

951 g

Auflage

1st ed. 2020

Sprache

Englisch

ISBN

978-3-030-52062-5

Beschreibung

Rezension

“The book presents with great detail the theory needed for estimation of linear functions of model parameters … . The exposition of so many general results for prediction is a significant feature of the book. I also found particularly interesting the detailed presentation of ANOVA formulae … . All these features make the book either a reference one or an excellent textbook for a graduate level course on linear models … .” (Vassilis G. S. Vasdekis, Mathematical Reviews, September, 2022)

“This is a classic book to modern linear algebra. It is primarily about linear tranformations and therefore most of the theorems and proofs work for modern linear algebra. The book does start from the beginning and assumes no prior knowledge of the subject. It is also extremely well-written and logical with short and elegant proofs. … The exercises are very good, and are a mixture of proof questions and concrete examples.” (Rózsa Horváth-Bokor, zbMATH 1462.62004, 2021)

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

03.11.2020

Verlag

Springer

Seitenzahl

504

Maße (L/B/H)

24.1/16/3.4 cm

Gewicht

951 g

Auflage

1st ed. 2020

Sprache

Englisch

ISBN

978-3-030-52062-5

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: Linear Model Theory
  • Preface.- 1 A Brief Introduction.- 2 Selected Matrix Algebra Topics and Results.- 3 Generalized Inverses and Solutions to Systems of Linear Equations.- 4 Moments of a Random Vector and of Linear and Quadratic Forms in a Random Vector.- 5 Types of Linear Models.- 6 Estimability.- 7 Least Squares Estimation for the Gauss-Markov Model.- 8 Least Squares Geometry and the Overall ANOVA.- 9 Least Squares Estimation and ANOVA for Partitioned Models.- 10 Constrained Least Squares Estimation and ANOVA.- 11 Best Linear Unbiased Estimation for the Aitken Model.- 12 Model Misspecification.- 13 Best Linear Unbiased Prediction.- 14 Distribution Theory.- 15 Inference for Estimable and Predictable Functions.- 16 Inference for Variance-Covariance Parameters.- 17 Empirical BLUE and BLUP.- Index.