Computer Based Numerical & Statistical Techniques
Author: Goyal
Publisher: Firewall Media
Published: 2005
Total Pages: 612
ISBN-13: 9788170087830
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Computer Based Numerical and Statistical Techniques
Author: Santosh Kumar Sengar
Publisher: S. Chand Publishing
Published:
Total Pages:
ISBN-13: 9352833988
DOWNLOAD EBOOKComputer Based Numerical and Statistical Techniques has been written to provide fundamental introduction of numerical analysis for the students who take a course on Engineering Mathematics and for the students of computer science engineering. The book has been divided into 14 chapters covering all important aspects starting from high speed computation to Interpolation and Curve Fitting to Numerical Integration and Differentiation and finally focusing on Test of Significance
A Handbook of Numerical and Statistical Techniques
Author: J. H. Pollard
Publisher: CUP Archive
Published: 1977
Total Pages: 372
ISBN-13: 9780521297509
DOWNLOAD EBOOKThis handbook is designed for experimental scientists, particularly those in the life sciences. It is for the non-specialist, and although it assumes only a little knowledge of statistics and mathematics, those with a deeper understanding will also find it useful. The book is directed at the scientist who wishes to solve his numerical and statistical problems on a programmable calculator, mini-computer or interactive terminal. The volume is also useful for the user of full-scale computer systems in that it describes how the large computer solves numerical and statistical problems. The book is divided into three parts. Part I deals with numerical techniques and Part II with statistical techniques. Part III is devoted to the method of least squares which can be regarded as both a statistical and numerical method. The handbook shows clearly how each calculation is performed. Each technique is illustrated by at least one example and there are worked examples and exercises throughout the volume.
Computer Based Numerical and Statistical Techniques
Author: Kumar Santosh
Publisher: S. Chand Publishing
Published: 2009
Total Pages: 0
ISBN-13: 9788121929394
DOWNLOAD EBOOKThe contents of this book have numerous distinguishing features over the already existing textbooks on the same topic.The contents of the book have been organized in a logical order and the topics are discussed in a systematic manner.The Book is designed as a textbook on computational numarical methods for the students of engineering,mathematics,BCA,MCA of different technical universities.
Numerical Methods of Statistics
Author: John F. Monahan
Publisher: Cambridge University Press
Published: 2011-04-18
Total Pages: 465
ISBN-13: 1139498002
DOWNLOAD EBOOKThis 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.
Elements of Statistical Computing
Author: R.A. Thisted
Publisher: Routledge
Published: 2017-10-19
Total Pages: 456
ISBN-13: 1351452746
DOWNLOAD EBOOKStatistics 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.
Numerical Analysis for Statisticians
Author: Kenneth Lange
Publisher: Springer Science & Business Media
Published: 2010-05-17
Total Pages: 606
ISBN-13: 1441959459
DOWNLOAD EBOOKNumerical 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.
COMPUTER ORIENTED NUMERICAL METHODS
Author: RAJARAMAN, V.
Publisher: PHI Learning Pvt. Ltd.
Published: 2018-11-01
Total Pages: 222
ISBN-13: 9388028325
DOWNLOAD EBOOKThis book is a concise and lucid introduction to computer oriented numerical methods with well-chosen graphical illustrations that give an insight into the mechanism of various methods. The book develops computational algorithms for solving non-linear algebraic equation, sets of linear equations, curve-fitting, integration, differentiation, and solving ordinary differential equations. OUTSTANDING FEATURES • Elementary presentation of numerical methods using computers for solving a variety of problems for students who have only basic level knowledge of mathematics. • Geometrical illustrations used to explain how numerical algorithms are evolved. • Emphasis on implementation of numerical algorithm on computers. • Detailed discussion of IEEE standard for representing floating point numbers. • Algorithms derived and presented using a simple English based structured language. • Truncation and rounding errors in numerical calculations explained. • Each chapter starts with learning goals and all methods illustrated with numerical examples. • Appendix gives pointers to open source libraries for numerical computation.
Numerical Issues in Statistical Computing for the Social Scientist
Author: Micah Altman
Publisher: John Wiley & Sons
Published: 2004-02-15
Total Pages: 349
ISBN-13: 0471475742
DOWNLOAD EBOOKAt 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.
Numerical Verification Methods and Computer-Assisted Proofs for Partial Differential Equations
Author: Mitsuhiro T. Nakao
Publisher: Springer Nature
Published: 2019-11-11
Total Pages: 469
ISBN-13: 9811376697
DOWNLOAD EBOOKIn the last decades, various mathematical problems have been solved by computer-assisted proofs, among them the Kepler conjecture, the existence of chaos, the existence of the Lorenz attractor, the famous four-color problem, and more. In many cases, computer-assisted proofs have the remarkable advantage (compared with a “theoretical” proof) of additionally providing accurate quantitative information. The authors have been working more than a quarter century to establish methods for the verified computation of solutions for partial differential equations, mainly for nonlinear elliptic problems of the form -∆u=f(x,u,∇u) with Dirichlet boundary conditions. Here, by “verified computation” is meant a computer-assisted numerical approach for proving the existence of a solution in a close and explicit neighborhood of an approximate solution. The quantitative information provided by these techniques is also significant from the viewpoint of a posteriori error estimates for approximate solutions of the concerned partial differential equations in a mathematically rigorous sense. In this monograph, the authors give a detailed description of the verified computations and computer-assisted proofs for partial differential equations that they developed. In Part I, the methods mainly studied by the authors Nakao and Watanabe are presented. These methods are based on a finite dimensional projection and constructive a priori error estimates for finite element approximations of the Poisson equation. In Part II, the computer-assisted approaches via eigenvalue bounds developed by the author Plum are explained in detail. The main task of this method consists of establishing eigenvalue bounds for the linearization of the corresponding nonlinear problem at the computed approximate solution. Some brief remarks on other approaches are also given in Part III. Each method in Parts I and II is accompanied by appropriate numerical examples that confirm the actual usefulness of the authors’ methods. Also in some examples practical computer algorithms are supplied so that readers can easily implement the verification programs by themselves.
