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Numerical Analysis Statistics
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Book Synopsis Numerical Analysis for Statisticians by : Kenneth Lange
Download or read book Numerical Analysis for Statisticians written by Kenneth Lange and published by Springer Science & Business Media. This book was released on 2010-05-17 with total page 606 pages. Available in PDF, EPUB and Kindle. Book excerpt: Numerical analysis is the study of computation and its accuracy, stability and often its implementation on a computer. This book focuses on the principles of numerical analysis and is intended to equip those readers who use statistics to craft their own software and to understand the advantages and disadvantages of different numerical methods.
Book Synopsis Numerical Methods of Statistics by : John F. Monahan
Download or read book Numerical Methods of Statistics written by John F. Monahan and published by Cambridge University Press. This book was released on 2011-04-18 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explains how computer software is designed to perform the tasks required for sophisticated statistical analysis. For statisticians, it examines the nitty-gritty computational problems behind statistical methods. For mathematicians and computer scientists, it looks at the application of mathematical tools to statistical problems. The first half of the book offers a basic background in numerical analysis that emphasizes issues important to statisticians. The next several chapters cover a broad array of statistical tools, such as maximum likelihood and nonlinear regression. The author also treats the application of numerical tools; numerical integration and random number generation are explained in a unified manner reflecting complementary views of Monte Carlo methods. Each chapter contains exercises that range from simple questions to research problems. Most of the examples are accompanied by demonstration and source code available from the author's website. New in this second edition are demonstrations coded in R, as well as new sections on linear programming and the Nelder–Mead search algorithm.
Book Synopsis Computational Methods for Numerical Analysis with R by : James P Howard, II
Download or read book Computational Methods for Numerical Analysis with R written by James P Howard, II and published by CRC Press. This book was released on 2017-07-12 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Methods for Numerical Analysis with R is an overview of traditional numerical analysis topics presented using R. This guide shows how common functions from linear algebra, interpolation, numerical integration, optimization, and differential equations can be implemented in pure R code. Every algorithm described is given with a complete function implementation in R, along with examples to demonstrate the function and its use. Computational Methods for Numerical Analysis with R is intended for those who already know R, but are interested in learning more about how the underlying algorithms work. As such, it is suitable for statisticians, economists, and engineers, and others with a computational and numerical background.
Book Synopsis Advances in Numerical Analysis Emphasizing Interval Data by : Tofigh Allahviranloo
Download or read book Advances in Numerical Analysis Emphasizing Interval Data written by Tofigh Allahviranloo and published by CRC Press. This book was released on 2022-02-18 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: Numerical analysis forms a cornerstone of numeric computing and optimization, in particular recently, interval numerical computations play an important role in these topics. The interest of researchers in computations involving uncertain data, namely interval data opens new avenues in coping with real-world problems and deliver innovative and efficient solutions. This book provides the basic theoretical foundations of numerical methods, discusses key technique classes, explains improvements and improvements, and provides insights into recent developments and challenges. The theoretical parts of numerical methods, including the concept of interval approximation theory, are introduced and explained in detail. In general, the key features of the book include an up-to-date and focused treatise on error analysis in calculations, in particular the comprehensive and systematic treatment of error propagation mechanisms, considerations on the quality of data involved in numerical calculations, and a thorough discussion of interval approximation theory. Moreover, this book focuses on approximation theory and its development from the perspective of linear algebra, and new and regular representations of numerical integration and their solutions are enhanced by error analysis as well. The book is unique in the sense that its content and organization will cater to several audiences, in particular graduate students, researchers, and practitioners.
Book Synopsis Numerical Analysis for Engineers and Scientists by : G. Miller
Download or read book Numerical Analysis for Engineers and Scientists written by G. Miller and published by Cambridge University Press. This book was released on 2014-05-29 with total page 583 pages. Available in PDF, EPUB and Kindle. Book excerpt: A graduate-level introduction balancing theory and application, providing full coverage of classical methods with many practical examples and demonstration programs.
Book Synopsis Numerical Analysis Using R by : Graham W. Griffiths
Download or read book Numerical Analysis Using R written by Graham W. Griffiths and published by Cambridge University Press. This book was released on 2016-04-26 with total page 637 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest numerical solutions to initial value problems and boundary value problems described by ODEs and PDEs. The author offers practical methods that can be adapted to solve wide ranges of problems and illustrates them in the increasingly popular open source computer language R, allowing integration with more statistically based methods. The book begins with standard techniques, followed by an overview of 'high resolution' flux limiters and WENO to solve problems with solutions exhibiting high gradient phenomena. Meshless methods using radial basis functions are then discussed in the context of scattered data interpolation and the solution of PDEs on irregular grids. Three detailed case studies demonstrate how numerical methods can be used to tackle very different complex problems. With its focus on practical solutions to real-world problems, this book will be useful to students and practitioners in all areas of science and engineering, especially those using R.
Book Synopsis Numerical Issues in Statistical Computing for the Social Scientist by : Micah Altman
Download or read book Numerical Issues in Statistical Computing for the Social Scientist written by Micah Altman and published by John Wiley & Sons. This book was released on 2004-02-15 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: At last—a social scientist's guide through the pitfalls of modern statistical computing Addressing the current deficiency in the literature on statistical methods as they apply to the social and behavioral sciences, Numerical Issues in Statistical Computing for the Social Scientist seeks to provide readers with a unique practical guidebook to the numerical methods underlying computerized statistical calculations specific to these fields. The authors demonstrate that knowledge of these numerical methods and how they are used in statistical packages is essential for making accurate inferences. With the aid of key contributors from both the social and behavioral sciences, the authors have assembled a rich set of interrelated chapters designed to guide empirical social scientists through the potential minefield of modern statistical computing. Uniquely accessible and abounding in modern-day tools, tricks, and advice, the text successfully bridges the gap between the current level of social science methodology and the more sophisticated technical coverage usually associated with the statistical field. Highlights include: A focus on problems occurring in maximum likelihood estimation Integrated examples of statistical computing (using software packages such as the SAS, Gauss, Splus, R, Stata, LIMDEP, SPSS, WinBUGS, and MATLAB®) A guide to choosing accurate statistical packages Discussions of a multitude of computationally intensive statistical approaches such as ecological inference, Markov chain Monte Carlo, and spatial regression analysis Emphasis on specific numerical problems, statistical procedures, and their applications in the field Replications and re-analysis of published social science research, using innovative numerical methods Key numerical estimation issues along with the means of avoiding common pitfalls A related Web site includes test data for use in demonstrating numerical problems, code for applying the original methods described in the book, and an online bibliography of Web resources for the statistical computation Designed as an independent research tool, a professional reference, or a classroom supplement, the book presents a well-thought-out treatment of a complex and multifaceted field.
Book Synopsis Afternotes on Numerical Analysis by : G. W. Stewart
Download or read book Afternotes on Numerical Analysis written by G. W. Stewart and published by SIAM. This book was released on 1996-01-01 with total page 183 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the central ideas of modern numerical analysis in a vivid and straightforward fashion with a minimum of fuss and formality. Stewart designed this volume while teaching an upper-division course in introductory numerical analysis. To clarify what he was teaching, he wrote down each lecture immediately after it was given. The result reflects the wit, insight, and verbal craftmanship which are hallmarks of the author. Simple examples are used to introduce each topic, then the author quickly moves on to the discussion of important methods and techniques. With its rich mixture of graphs and code segments, the book provides insights and advice that help the reader avoid the many pitfalls in numerical computation that can easily trap an unwary beginner. Written by a leading expert in numerical analysis, this book is certain to be the one you need to guide you through your favorite textbook.
Book Synopsis Introduction to Numerical Analysis by : John Gregory
Download or read book Introduction to Numerical Analysis written by John Gregory and published by Jones & Bartlett Publishers. This book was released on 1994 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Numerical Methods of Statistics by : John F. Monahan
Download or read book Numerical Methods of Statistics written by John F. Monahan and published by Cambridge University Press. This book was released on 2001-02-05 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 2001 book provides a basic background in numerical analysis and its applications in statistics.
Book Synopsis Elements of Statistical Computing by : R.A. Thisted
Download or read book Elements of Statistical Computing written by R.A. Thisted and published by Routledge. This book was released on 2017-10-19 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistics and computing share many close relationships. Computing now permeates every aspect of statistics, from pure description to the development of statistical theory. At the same time, the computational methods used in statistical work span much of computer science. Elements of Statistical Computing covers the broad usage of computing in statistics. It provides a comprehensive account of the most important computational statistics. Included are discussions of numerical analysis, numerical integration, and smoothing. The author give special attention to floating point standards and numerical analysis; iterative methods for both linear and nonlinear equation, such as Gauss-Seidel method and successive over-relaxation; and computational methods for missing data, such as the EM algorithm. Also covered are new areas of interest, such as the Kalman filter, projection-pursuit methods, density estimation, and other computer-intensive techniques.
Book Synopsis C Programming: The Essentials for Engineers and Scientists by : David R. Brooks
Download or read book C Programming: The Essentials for Engineers and Scientists written by David R. Brooks and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text teaches the essentials of C programming, concentrating on what readers need to know in order to produce stand-alone programs and so solve typical scientific and engineering problems. It is a learning-by-doing book, with many examples and exercises, and lays a foundation of scientific programming concepts and techniques that will prove valuable for those who might eventually move on to another language. Written for undergraduates who are familiar with computers and typical applications but are new to programming.
Book Synopsis Using R for Numerical Analysis in Science and Engineering by : Victor A. Bloomfield
Download or read book Using R for Numerical Analysis in Science and Engineering written by Victor A. Bloomfield and published by CRC Press. This book was released on 2018-09-03 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Instead of presenting the standard theoretical treatments that underlie the various numerical methods used by scientists and engineers, Using R for Numerical Analysis in Science and Engineering shows how to use R and its add-on packages to obtain numerical solutions to the complex mathematical problems commonly faced by scientists and engineers. This practical guide to the capabilities of R demonstrates Monte Carlo, stochastic, deterministic, and other numerical methods through an abundance of worked examples and code, covering the solution of systems of linear algebraic equations and nonlinear equations as well as ordinary differential equations and partial differential equations. It not only shows how to use R’s powerful graphic tools to construct the types of plots most useful in scientific and engineering work, but also: Explains how to statistically analyze and fit data to linear and nonlinear models Explores numerical differentiation, integration, and optimization Describes how to find eigenvalues and eigenfunctions Discusses interpolation and curve fitting Considers the analysis of time series Using R for Numerical Analysis in Science and Engineering provides a solid introduction to the most useful numerical methods for scientific and engineering data analysis using R.
Book Synopsis A History of Numerical Analysis from the 16th through the 19th Century by : H. H. Goldstine
Download or read book A History of Numerical Analysis from the 16th through the 19th Century written by H. H. Goldstine and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book I have attempted to trace the development of numerical analysis during the period in which the foundations of the modern theory were being laid. To do this I have had to exercise a certain amount of selectivity in choosing and in rejecting both authors and papers. I have rather arbitrarily chosen, in the main, the most famous mathematicians of the period in question and have concentrated on their major works in numerical analysis at the expense, perhaps, of other lesser known but capable analysts. This selectivity results from the need to choose from a large body of literature, and from my feeling that almost by definition the great masters of mathematics were the ones responsible for the most significant accomplishments. In any event I must accept full responsibility for the choices. I would particularly like to acknowledge my thanks to Professor Otto Neugebauer for his help and inspiration in the preparation of this book. This consisted of many friendly discussions that I will always value. I should also like to express my deep appreciation to the International Business Machines Corporation of which I have the honor of being a Fellow and in particular to Dr. Ralph E. Gomory, its Vice-President for Research, for permitting me to undertake the writing of this book and for helping make it possible by his continuing encouragement and support.
Download or read book Optimization written by Kenneth Lange and published by Springer Science & Business Media. This book was released on 2004-06-17 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lange is a Springer author of other successful books. This is the first book that emphasizes the applications of optimization to statistics. The emphasis on statistical applications will be especially appealing to graduate students of statistics and biostatistics.
Book Synopsis Assessment of Treatment Plant Performance and Water Quality Data: A Guide for Students, Researchers and Practitioners by : Marcos von Sperling
Download or read book Assessment of Treatment Plant Performance and Water Quality Data: A Guide for Students, Researchers and Practitioners written by Marcos von Sperling and published by IWA Publishing. This book was released on 2020-01-15 with total page 668 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the basic principles for evaluating water quality and treatment plant performance in a clear, innovative and didactic way, using a combined approach that involves the interpretation of monitoring data associated with (i) the basic processes that take place in water bodies and in water and wastewater treatment plants and (ii) data management and statistical calculations to allow a deep interpretation of the data. This book is problem-oriented and works from practice to theory, covering most of the information you will need, such as (a) obtaining flow data and working with the concept of loading, (b) organizing sampling programmes and measurements, (c) connecting laboratory analysis to data management, (e) using numerical and graphical methods for describing monitoring data (descriptive statistics), (f) understanding and reporting removal efficiencies, (g) recognizing symmetry and asymmetry in monitoring data (normal and log-normal distributions), (h) evaluating compliance with targets and regulatory standards for effluents and water bodies, (i) making comparisons with the monitoring data (tests of hypothesis), (j) understanding the relationship between monitoring variables (correlation and regression analysis), (k) making water and mass balances, (l) understanding the different loading rates applied to treatment units, (m) learning the principles of reaction kinetics and reactor hydraulics and (n) performing calibration and verification of models. The major concepts are illustrated by 92 fully worked-out examples, which are supported by 75 freely-downloadable Excel spreadsheets. Each chapter concludes with a checklist for your report. If you are a student, researcher or practitioner planning to use or already using treatment plant and water quality monitoring data, then this book is for you! 75 Excel spreadsheets are available to download.
Book Synopsis An Introduction to Numerical Methods and Analysis by : James F. Epperson
Download or read book An Introduction to Numerical Methods and Analysis written by James F. Epperson and published by John Wiley & Sons. This book was released on 2013-06-06 with total page 579 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition ". . . outstandingly appealing with regard to its style, contents, considerations of requirements of practice, choice of examples, and exercises." —Zentrablatt Math ". . . carefully structured with many detailed worked examples . . ." —The Mathematical Gazette ". . . an up-to-date and user-friendly account . . ." —Mathematika An Introduction to Numerical Methods and Analysis addresses the mathematics underlying approximation and scientific computing and successfully explains where approximation methods come from, why they sometimes work (or don't work), and when to use one of the many techniques that are available. Written in a style that emphasizes readability and usefulness for the numerical methods novice, the book begins with basic, elementary material and gradually builds up to more advanced topics. A selection of concepts required for the study of computational mathematics is introduced, and simple approximations using Taylor's Theorem are also treated in some depth. The text includes exercises that run the gamut from simple hand computations, to challenging derivations and minor proofs, to programming exercises. A greater emphasis on applied exercises as well as the cause and effect associated with numerical mathematics is featured throughout the book. An Introduction to Numerical Methods and Analysis is the ideal text for students in advanced undergraduate mathematics and engineering courses who are interested in gaining an understanding of numerical methods and numerical analysis.
