Functional Approach to Optimal Experimental Design Functional Approach to Optimal Experimental Design
Lecture Notes in Statistics

Functional Approach to Optimal Experimental Design

    • ‏89٫99 US$
    • ‏89٫99 US$

وصف الناشر

The book presents a novel approach for studying optimal experimental designs. The functional approach consists of representing support points of the designs by Taylor series. It is thoroughly explained for many linear and nonlinear regression models popular in practice including polynomial, trigonometrical, rational, and exponential models. Using the tables of coefficients of these series included in the book, a reader can construct optimal designs for specific models by hand.

The book is suitable for researchers in statistics and especially in experimental design theory as well as to students and practitioners with a good mathematical background.

Viatcheslav B. Melas is Professor of Statistics and Numerical Analysis at the St. Petersburg State University and the author of more than one hundred scientific articles and four books. He is an Associate Editor of the Journal of Statistical Planning and Inference and Co-Chair of the organizing committee of the 1st–5th St. Petersburg Workshops on Simulation (1994, 1996, 1998, 2001 and 2005).

النوع
علم وطبيعة
تاريخ النشر
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٢٠ أبريل
اللغة
EN
الإنجليزية
عدد الصفحات
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الناشر
Springer New York
البائع
Springer Nature B.V.
الحجم
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‫م.ب.‬
Optimal Design and Related Areas in Optimization and Statistics Optimal Design and Related Areas in Optimization and Statistics
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Interpolation and Extrapolation Optimal Designs 2 Interpolation and Extrapolation Optimal Designs 2
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The Moment-SOS Hierarchy The Moment-SOS Hierarchy
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Stochastic Linear Programming Stochastic Linear Programming
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Optimization and Control with Applications Optimization and Control with Applications
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Continuous Optimization Continuous Optimization
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Statistical Modeling and Simulation for Experimental Design and Machine Learning Applications Statistical Modeling and Simulation for Experimental Design and Machine Learning Applications
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Statistics and Simulation Statistics and Simulation
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Case Studies in Spatial Point Process Modeling Case Studies in Spatial Point Process Modeling
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Benchmarking, Temporal Distribution, and Reconciliation Methods for Time Series Benchmarking, Temporal Distribution, and Reconciliation Methods for Time Series
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Dependence in Probability and Statistics Dependence in Probability and Statistics
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Restricted Parameter Space Estimation Problems Restricted Parameter Space Estimation Problems
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The Nature of Statistical Evidence The Nature of Statistical Evidence
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Weak Dependence: With Examples and Applications Weak Dependence: With Examples and Applications
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