Analytical And Computational Methods In Probability Theory PDF Download
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| Author | : Vladimir V. Rykov |
| Publisher | : Springer |
| Total Pages | : 540 |
| Release | : 2017-12-21 |
| Genre | : Computers |
| ISBN | : 3319715046 |
Download Analytical and Computational Methods in Probability Theory Book in PDF, ePub and Kindle
This book constitutes the refereed proceedings of the First International Conference on Analytical and Computational Methods in Probability Theory and its Applications, ACMPT 2017, held in Moscow, Russia, in October 2017. The 42 full papers presented were carefully reviewed and selected from 173 submissions. The conference program consisted of four main themes associated with significant contributions made by A.D.Soloviev. These are: Analytical methods in probability theory, Computational methods in probability theory, Asymptotical methods in probability theory, the history of mathematics.
| Author | : Siegmund Brandt |
| Publisher | : Amsterdam : North-Holland Publishing Company ; New York : American Elsevier Publishing Company |
| Total Pages | : 440 |
| Release | : 1976 |
| Genre | : Mathematics |
| ISBN | : |
Download Statistical and Computational Methods in Data Analysis Book in PDF, ePub and Kindle
Probabilities; Random variables: distributions of a random variable; Distributions of several random variables; Some important distributions and theorems; Sampling; The method of "maximum likelihood"; Testing of statistical hypotheses; The method of least squares; Some remarks on minimization; Analysis of variance; Linear regression; Time series analysis.
| Author | : Siegmund Brandt |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 523 |
| Release | : 2014-02-14 |
| Genre | : Science |
| ISBN | : 3319037625 |
Download Data Analysis Book in PDF, ePub and Kindle
The fourth edition of this successful textbook presents a comprehensive introduction to statistical and numerical methods for the evaluation of empirical and experimental data. Equal weight is given to statistical theory and practical problems. The concise mathematical treatment of the subject matter is illustrated by many examples and for the present edition a library of Java programs has been developed. It comprises methods of numerical data analysis and graphical representation as well as many example programs and solutions to programming problems. The book is conceived both as an introduction and as a work of reference. In particular it addresses itself to students, scientists and practitioners in science and engineering as a help in the analysis of their data in laboratory courses, in working for bachelor or master degrees, in thesis work, and in research and professional work.
| Author | : George Anastassiou |
| Publisher | : CRC Press |
| Total Pages | : 413 |
| Release | : 2019-06-03 |
| Genre | : Mathematics |
| ISBN | : 0429525117 |
Download Handbook of Analytic Computational Methods in Applied Mathematics Book in PDF, ePub and Kindle
Working computationally in applied mathematics is the very essence of dealing with real-world problems in science and engineering. Approximation theory-on the borderline between pure and applied mathematics- has always supplied some of the most innovative ideas, computational methods, and original approaches to many types of problems. The f
| Author | : John H. Drew |
| Publisher | : Springer |
| Total Pages | : 336 |
| Release | : 2016-12-15 |
| Genre | : Business & Economics |
| ISBN | : 3319433237 |
Download Computational Probability Book in PDF, ePub and Kindle
This new edition includes the latest advances and developments in computational probability involving A Probability Programming Language (APPL). The book examines and presents, in a systematic manner, computational probability methods that encompass data structures and algorithms. The developed techniques address problems that require exact probability calculations, many of which have been considered intractable in the past. The book addresses the plight of the probabilist by providing algorithms to perform calculations associated with random variables. Computational Probability: Algorithms and Applications in the Mathematical Sciences, 2nd Edition begins with an introductory chapter that contains short examples involving the elementary use of APPL. Chapter 2 reviews the Maple data structures and functions necessary to implement APPL. This is followed by a discussion of the development of the data structures and algorithms (Chapters 3–6 for continuous random variables and Chapters 7–9 for discrete random variables) used in APPL. The book concludes with Chapters 10–15 introducing a sampling of various applications in the mathematical sciences. This book should appeal to researchers in the mathematical sciences with an interest in applied probability and instructors using the book for a special topics course in computational probability taught in a mathematics, statistics, operations research, management science, or industrial engineering department.
| Author | : John H. Drew |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 220 |
| Release | : 2008-01-08 |
| Genre | : Mathematics |
| ISBN | : 0387746765 |
Download Computational Probability Book in PDF, ePub and Kindle
This title organizes computational probability methods into a systematic treatment. The book examines two categories of problems. "Algorithms for Continuous Random Variables" covers data structures and algorithms, transformations of random variables, and products of independent random variables. "Algorithms for Discrete Random Variables" discusses data structures and algorithms, sums of independent random variables, and order statistics.
| Author | : Dan Gabriel Cacuci |
| Publisher | : CRC Press |
| Total Pages | : 372 |
| Release | : 2016-04-19 |
| Genre | : Mathematics |
| ISBN | : 1584887362 |
Download Computational Methods for Data Evaluation and Assimilation Book in PDF, ePub and Kindle
Data evaluation and data combination require the use of a wide range of probability theory concepts and tools, from deductive statistics mainly concerning frequencies and sample tallies to inductive inference for assimilating non-frequency data and a priori knowledge. Computational Methods for Data Evaluation and Assimilation presents interdiscipli
| Author | : Matteo Grigoletto |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 228 |
| Release | : 2013-01-26 |
| Genre | : Mathematics |
| ISBN | : 884702871X |
Download Complex Models and Computational Methods in Statistics Book in PDF, ePub and Kindle
The use of computational methods in statistics to face complex problems and highly dimensional data, as well as the widespread availability of computer technology, is no news. The range of applications, instead, is unprecedented. As often occurs, new and complex data types require new strategies, demanding for the development of novel statistical methods and suggesting stimulating mathematical problems. This book is addressed to researchers working at the forefront of the statistical analysis of complex systems and using computationally intensive statistical methods.
| Author | : Dugue |
| Publisher | : |
| Total Pages | : 200 |
| Release | : 2014-01-15 |
| Genre | : |
| ISBN | : 9783662135136 |
Download Analytical Methods in Probability Theory Book in PDF, ePub and Kindle
| Author | : Michael Mitzenmacher |
| Publisher | : Cambridge University Press |
| Total Pages | : 372 |
| Release | : 2005-01-31 |
| Genre | : Computers |
| ISBN | : 9780521835404 |
Download Probability and Computing Book in PDF, ePub and Kindle
Randomization and probabilistic techniques play an important role in modern computer science, with applications ranging from combinatorial optimization and machine learning to communication networks and secure protocols. This 2005 textbook is designed to accompany a one- or two-semester course for advanced undergraduates or beginning graduate students in computer science and applied mathematics. It gives an excellent introduction to the probabilistic techniques and paradigms used in the development of probabilistic algorithms and analyses. It assumes only an elementary background in discrete mathematics and gives a rigorous yet accessible treatment of the material, with numerous examples and applications. The first half of the book covers core material, including random sampling, expectations, Markov's inequality, Chevyshev's inequality, Chernoff bounds, the probabilistic method and Markov chains. The second half covers more advanced topics such as continuous probability, applications of limited independence, entropy, Markov chain Monte Carlo methods and balanced allocations. With its comprehensive selection of topics, along with many examples and exercises, this book is an indispensable teaching tool.
