A brand new, fully updated edition of a popular classic on matrix differential calculus with applications in statistics and econometrics
This exhaustive, self-contained book on matrix theory and matrix differential calculus provides a treatment of matrix calculus based on differentials and shows how easy it is to use this theory once you have mastered the technique. Jan Magnus, who, along with the late Heinz Neudecker, pioneered the theory, develops it further in this new edition and provides many examples along the way to support it.
Matrix calculus has become an essential tool for quantitative methods in a large number of applications, ranging from social and behavioral sciences to econometrics. It is still relevant and used today in a wide range of subjects such as the biosciences and psychology. Matrix Differential Calculus with Applications in Statistics and Econometrics, Third Edition contains all of the essentials of multivariable calculus with an emphasis on the use of differentials. It starts by presenting a concise, yet thorough overview of matrix algebra, then goes on to develop the theory of differentials. The rest of the text combines the theory and application of matrix differential calculus, providing the practitioner and researcher with both a quick review and a detailed reference.
Fulfills the need for an updated and unified treatment of matrix differential calculus
Contains many new examples and exercises based on questions asked of the author over the years
Covers new developments in field and features new applications
Written by a leading expert and pioneer of the theory
Part of the Wiley Series in Probability and Statistics
Matrix Differential Calculus With Applications in Statistics and Econometrics Third Edition is an ideal text for graduate students and academics studying the subject, as well as for postgraduates and specialists working in biosciences and psychology.
Описание: Contains 41 reviewed papers, selected by the two program committees from a total of 101 submissions. Among the issues addressed are design and analysis of approximation algorithms, hardness of approximation, small space and data streaming algorithms, sub-linear time algorithms, embeddings and metric space methods, and more.
Описание: Constitutes the joint refereed proceedings of the 11th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2008 and the 12th International Workshop on Randomization and Computation, RANDOM 2008, held in Boston, MA, USA, in August 2008. This book reviews 20 revised papers of the APPROX 2008 workshop.
Описание: These are the joint refereed proceedings of the 4th International Workshop on Approximation Algorithms for Optimization Problems, APPROX 2001 and of the 5th International Workshop on Randomization and Approximation Techniques in Computer Science, RANDOM 2001.
Автор: Klaus Jansen; Stefano Leonardi; Vijay Vazirani Название: Approximation Algorithms for Combinatorial Optimization ISBN: 3540441867 ISBN-13(EAN): 9783540441861 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Compiled from the proceedings of the 5th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, this volume contains 20 revised full papers. Coverage includes design and analysis of approximation algorithms, inapproximability results and online problems.
Описание: This text presents various new results within the areas covered by the workshop.
Автор: Klaus Jansen; Samir Khuller Название: Approximation Algorithms for Combinatorial Optimization ISBN: 3540679960 ISBN-13(EAN): 9783540679967 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The topics dealt with include design and analysis of approximation algorithms, inapproximibility results, randomization techniques, average-case analysis, scheduling problems, cuts and connectivity, packing and covering, geometric problems, network design, and various applications.
Автор: Harold Kushner; G. George Yin Название: Stochastic Approximation and Recursive Algorithms and Applications ISBN: 1441918477 ISBN-13(EAN): 9781441918475 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents a thorough development of the modern theory of stochastic approximation or recursive stochastic algorithms for both constrained and unconstrained problems. This second edition is a thorough revision, although the main features and structure remain unchanged.
Автор: Panos M. Pardalos Название: Approximation and Complexity in Numerical Optimization ISBN: 1441948295 ISBN-13(EAN): 9781441948298 Издательство: Springer Рейтинг: Цена: 41787.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: On the other hand, computational complexity, originating from the interactions between computer science and numeri- cal optimization, is one of the major theories that have revolutionized the approach to solving optimization problems and to analyzing their intrinsic difficulty.
Описание: This book comprises papers on diverse aspects of fuzzy logic, neural networks, and nature-inspired optimization meta-heuristics and their application in various areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. The book is organized into seven main parts, each with a collection of papers on a similar subject. The first part presents new concepts and algorithms based on type-2 fuzzy logic for dynamic parameter adaptation in meta-heuristics. The second part discusses network theory and applications, and includes papers describing applications of neural networks in diverse areas, such as time series prediction and pattern recognition. The third part addresses the theory and practice of meta-heuristics in different areas of application, while the fourth part describes diverse fuzzy logic applications in the control area, which can be considered as intelligent controllers. The next two parts explore applications in areas, such as time series prediction, and pattern recognition and new optimization and evolutionary algorithms and their applications respectively. Lastly, the seventh part addresses the design and application of different hybrid intelligent systems.
Автор: Arora Rajesh Kumar Название: Optimization: Algorithms and Applications ISBN: 1498721125 ISBN-13(EAN): 9781498721127 Издательство: Taylor&Francis Рейтинг: Цена: 29093.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Choose the Correct Solution Method for Your Optimization Problem
Optimization: Algorithms and Applications presents a variety of solution techniques for optimization problems, emphasizing concepts rather than rigorous mathematical details and proofs.
The book covers both gradient and stochastic methods as solution techniques for unconstrained and constrained optimization problems. It discusses the conjugate gradient method, Broyden-Fletcher-Goldfarb-Shanno algorithm, Powell method, penalty function, augmented Lagrange multiplier method, sequential quadratic programming, method of feasible directions, genetic algorithms, particle swarm optimization (PSO), simulated annealing, ant colony optimization, and tabu search methods. The author shows how to solve non-convex multi-objective optimization problems using simple modifications of the basic PSO code. The book also introduces multidisciplinary design optimization (MDO) architectures--one of the first optimization books to do so--and develops software codes for the simplex method and affine-scaling interior point method for solving linear programming problems. In addition, it examines Gomory's cutting plane method, the branch-and-bound method, and Balas' algorithm for integer programming problems.
The author follows a step-by-step approach to developing the MATLAB(R) codes from the algorithms. He then applies the codes to solve both standard functions taken from the literature and real-world applications, including a complex trajectory design problem of a robot, a portfolio optimization problem, and a multi-objective shape optimization problem of a reentry body. This hands-on approach improves your understanding and confidence in handling different solution methods. The MATLAB codes are available on the book's CRC Press web page.
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