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Authors: Dinh The Luc (2016) - This book introduces the reader to the field of multiobjective optimization through problems with simple structures, namely those in which the objective function and constraints are linear. Fundamental notions as well as state-of-the-art advances are presented in a comprehensive way and illustrated with the help of numerous examples. Three of the most popular methods for solving multiobjective linear problems are explained, and exercises are provided at the end of each chapter, helping students to grasp and apply key concepts and methods to more complex problems. The book was motivated by the fact that the majority of the practical problems we encounter in management science, engineer...
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Authors: Trần Vũ Thiệu (2011) - Lý thuyết chung về bài toán tối ưu, giải tích lồi, điều kiện tối ưu, bài toán ngẫu hứng. Phương pháp tìm cực tiểu không ràng buộc và có ràng buộc, phương pháp không dùng đạo hàm, phương pháp gradient, phương pháp tuyến tính hoá..
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Authors: Đào Hữu Hồ (2007) - Một số khái niệm, kết quả cơ bản của xác suất và thống kê xã hội được trình bày qua các bài toán giải tích tổ hợp, phép thử và biến cố, biến ngẫu nhiên, hàm phân phối, các số đặc trưng của biến ngẫu nhiên, lí thuyết mẫu, ước lượng đơn giản, bài toán kiểm định giả thiết đơn giản, tương quan và hồi qui..
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Authors: Patrice Bertail (2006) - Gives an account of the developments in the field of probability and statistics for dependent data. This book covers a range of topics from Markov chain theory and weak dependence with an emphasis on some developments on dynamical systems, to strong dependence in times series and random fields
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Authors: Y. Suhov; M. Kelbert (2005) - Probability and Statistics are as much about intuition and problem solving, as they are about theorem proving. Because of this, students can find it very difficult to make a successful transition from lectures to examinations to practice, since the problems involved can vary so much in nature.
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Authors: Morris H. DeGroot (1986) - The revision of this well-respected text presents a balance of the classical and Bayesian methods. The theoretical and practical sides of both probability and statistics are considered. New content areas include the Vorel- Kolmogorov Paradox, Confidence Bands for the Regression Line, the Correction for Continuity, and the Delta Method.
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Authors: Mark Zegarelli (2022) - Offers explanations of concepts such as whole numbers, fractions, decimals, and percents, and covers advanced topics including imaginary numbers, variables, and algebraic equations
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Authors: John J. Kinney (2009) - This handy book contains introductory explanations of the major topics in probability and statistics, including hypothesis testing and regression, while also delving into more advanced topics such as the analysis of sample surveys, analysis of experimental data, and statistical process control. The book recognizes that there are many sampling techniques that can actually improve on simple random sampling, and in addition, an introduction to the design of experiments is provided to reflect recent advances in conducting scientific experiments. This blend of coverage results in the development of a deeper understanding and solid foundation for the study of probability statistics. --
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Authors: Robert Bartoszynski (2008) - Provides a mathematical framework that permits students to carry out various procedures using any number of computer software packages as opposed to relying on one particular package
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Authors: John Tabak (2004) - A primer on probability and statistics that includes a chronology of notable events, a glossary of terms, and an array of sources for further research
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Authors: Nitis Mukhopadhyay (2000) - This textbook reveals the rigorous theory of probability and statistical inference in the style of a tutorial, using worked examples, exercises, numerous figures and tables, and computer simulations to develop and illustrate concepts - reinforcing important ideas and emphasizing special techniques with drills and boxed summaries
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Authors: Luis Manuel Cruz-Orive (2024) - This book presents a comprehensive set of methods for quantifying geometric quantities such as the volume of a tumor, the total surface area of the alveoli in a lung, the length of plant roots, or of blood vessels, the number of neurons in a brain compartment, the connectivity number of trabecular bone, the mean size of grains in a rock, etc..
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Authors: David G. Luenberger (2016) - This new edition covers the central concepts of practical optimization techniques, with an emphasis on methods that are both state-of-the-art and popular. Again a connection between the purely analytical character of an optimization problem and the behavior of algorithms used to solve the problem. As in the earlier editions, the material in this fourth edition is organized into three separate parts. Part I is a self-contained introduction to linear programming covering numerical algorithms and many of its important special applications. Part II, which is independent of Part I, covers the theory of unconstrained optimization, including both derivations of the appropriate optimality con...
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Authors: Nông Quốc Chinh (2003) - Trình bày lí thuyết và bài tập về không gian mêtric, không gian tôpô, các lớp không gian tôpô
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Authors: Nguyễn Thị Bạch Kim (2008) - Trình bày các kiến thức lí thuyết phương pháp tối ưu cơ bản và ứng dụng để giải quyết các bài toán tối ưu như: giải tích lồi, quy hoạch tuyến tính, quy hoạch nguyên và các bài toán tối ưu
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Authors: William W. Cooper (2007) - This volume systematically details both the basic principles and new developments in Data Envelopment Analysis (DEA), offering a solid understanding of the methodology, its uses, and its potential. New material in this edition includes coverage of recent developments that have greatly extended the power and scope of DEA and have lead to new directions for research and DEA uses. Each chapter accompanies its developments with simple numerical examples and discussions of actual applications. The first nine chapters cover the basic principles of DEA, while the final seven chapters provide a more advanced treatment.
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Authors: Tetsuzo Tanino; Hirotaka Nakayama; Yoshikazu Sawarag (1985) - In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation; methods for low-rank matrix approximations; hybrid methods based on a combination of iterative procedures and best o...
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Authors: Campbell, Michael J (2023) - In the sixteen years since the second edition of Statistics at Square Two was published, there have been many developments in statistical methodology and in methods of presenting statistics. MJC is pleased that his colleague Richard Jacques, who has considerable experience in more advanced statistical methods and teaching medical statistics to non- statisticians, has joined him as a co-author. Most of the examples have been updated and two new chapters have been added on meta-analysis and on time series analysis. In addition, reference is made to the many checklists which have appeared since the last edition to enable better reporting of research. This book is intended to build on the...
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Authors: Loftus, Stephen C (2022) - Basic Statistics with R: Reaching Decisions with Data provides an understanding of the processes at work in using data for results. Sections cover data collection and discuss exploratory analyses, including visual graphs, numerical summaries, and relationships between variables - basic probability, and statistical inference - including hypothesis testing and confidence intervals.
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Authors: Duffy, Daniel J (2022) - Ordinary differential equations and partial differential equations form the basis for modelling many kinds of phenomena in areas such as science, engineering, computational finance and more generally, mathematical physics. There are currently no books on the market which can guide a reader with no prior knowledge of PDEs through the basics and onto advanced applications."
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