Cantitate/Preț
Produs

Model-Oriented Design of Experiments: Lecture Notes in Statistics

Autor Peter Hackl, Valerii V. Fedorov
en Limba Engleză Paperback – 27 dec 2024
Topics include designs for nonlinear models, models with random parameters and models with correlated observations, designs for model discrimination and misspecified (contaminated) models, and designs in functional spaces.The authors avoid technical details, assuming a moderate background in calculus, matrix algebra, and statistics.
Citește tot Restrânge

Toate formatele și edițiile

Toate formatele și edițiile Preț Express
Paperback (2) 59489 lei  18-23 zile +5242 lei  6-12 zile
  Springer – 27 dec 2024 59489 lei  18-23 zile +5242 lei  6-12 zile
  Springer – 20 iun 1997 60749 lei  3-5 săpt.

Din seria Lecture Notes in Statistics

Preț: 59489 lei

Preț vechi: 74362 lei
-20% Nou

Puncte Express: 892

Preț estimativ în valută:
10525 12374$ 9218£

Carte disponibilă

Livrare economică 05-10 ianuarie 26
Livrare express 24-30 decembrie pentru 6241 lei

Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9781071643013
ISBN-10: 1071643010
Pagini: 152
Dimensiuni: 155 x 235 x 9 mm
Greutate: 0.24 kg
Ediția:Second Edition 2025
Editura: Springer
Seria Lecture Notes in Statistics


Cuprins

1 Some Facts From Regression Analysis.- 1.1 The Linear Model.- 1.2 More about the Information Matrix.- 1.3 Generalized Versions of the Linear Regression Model.- 1.4 Nonlinear Models.- 2 Convex Design Theory.- 2.1 Optimality Criteria.- 2.2 Some Properties of Optimality Criteria.- 2.3 Continuous Optimal Designs.- 2.4 The Sensitivity Function and Equivalence Theorems.- 2.5 Some Examples.- 2.6 Complements.- 3 Numerical Techniques.- 3.1 First Order Algorithm:D-criterion.- 3.2 First Order Algorithm: The General Case.- 3.3 Finite Sample Size.- 4 Optimal Design under Constraints.- 4.1 Cost Constraints.- 4.2 Constraints for Auxiliary Criteria.- 4.3 Directly Constrained Design Measures.- 5 Special Cases and Applications.- 5.1 Designs for Time-Dependent Models.- 5.2 Regression Models with Random Parameters.- 5.3 Mixed Models and Correlated Observations.- 5.4 Design for “Contaminated” Models.- 5.5 Model Discrimination.- 5.6 Nonlinear Regression.- 5.7 Design in Functional. Spaces.- A Some Results from Matrix Algebra.- B List of Symbols.- References.