Numerical Analysis for Statisticians

Numerical Analysis for Statisticians
Author: Kenneth Lange
Publisher: Springer Science & Business Media
Total Pages: 606
Release: 2010-05-17
Genre: Business & Economics
ISBN: 1441959459

Download Numerical Analysis for Statisticians Book in PDF, Epub and Kindle

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.

Numerical Analysis for Statisticians

Numerical Analysis for Statisticians
Author: Kenneth Lange
Publisher: Springer Science & Business Media
Total Pages: 606
Release: 2010-06-15
Genre: Business & Economics
ISBN: 1441959440

Download Numerical Analysis for Statisticians Book in PDF, Epub and Kindle

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.

Numerical Methods of Statistics

Numerical Methods of Statistics
Author: John F. Monahan
Publisher: Cambridge University Press
Total Pages: 465
Release: 2011-04-18
Genre: Computers
ISBN: 1139498002

Download Numerical Methods of Statistics Book in PDF, Epub and Kindle

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.

Computational Methods for Numerical Analysis with R

Computational Methods for Numerical Analysis with R
Author: James P Howard, II
Publisher: CRC Press
Total Pages: 257
Release: 2017-07-12
Genre: Mathematics
ISBN: 1498723640

Download Computational Methods for Numerical Analysis with R Book in PDF, Epub and Kindle

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.

Numerical Analysis for Statisticians

Numerical Analysis for Statisticians
Author: Kenneth Lange
Publisher: Springer Science & Business Media
Total Pages: 376
Release: 1999
Genre: Mathematics
ISBN: 9780387949796

Download Numerical Analysis for Statisticians Book in PDF, Epub and Kindle

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.

Numerical Methods of Statistics

Numerical Methods of Statistics
Author: John F. Monahan
Publisher: Cambridge University Press
Total Pages: 446
Release: 2001-02-05
Genre: Computers
ISBN: 9780521791687

Download Numerical Methods of Statistics Book in PDF, Epub and Kindle

This 2001 book provides a basic background in numerical analysis and its applications in statistics.

Numerical Issues in Statistical Computing for the Social Scientist

Numerical Issues in Statistical Computing for the Social Scientist
Author: Micah Altman
Publisher: John Wiley & Sons
Total Pages: 323
Release: 2004-02-15
Genre: Mathematics
ISBN: 0471475742

Download Numerical Issues in Statistical Computing for the Social Scientist Book in PDF, Epub and Kindle

At last—a social scientist's guide through the pitfalls ofmodern statistical computing Addressing the current deficiency in the literature onstatistical methods as they apply to the social and behavioralsciences, Numerical Issues in Statistical Computing for the SocialScientist seeks to provide readers with a unique practicalguidebook to the numerical methods underlying computerizedstatistical calculations specific to these fields. The authorsdemonstrate that knowledge of these numerical methods and how theyare used in statistical packages is essential for making accurateinferences. With the aid of key contributors from both the socialand behavioral sciences, the authors have assembled a rich set ofinterrelated chapters designed to guide empirical social scientiststhrough the potential minefield of modern statisticalcomputing. Uniquely accessible and abounding in modern-day tools, tricks,and advice, the text successfully bridges the gap between thecurrent level of social science methodology and the moresophisticated technical coverage usually associated with thestatistical field. Highlights include: A focus on problems occurring in maximum likelihoodestimation Integrated examples of statistical computing (using softwarepackages 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 intensivestatistical approaches such as ecological inference, Markov chainMonte Carlo, and spatial regression analysis Emphasis on specific numerical problems, statisticalprocedures, and their applications in the field Replications and re-analysis of published social scienceresearch, using innovative numerical methods Key numerical estimation issues along with the means ofavoiding common pitfalls A related Web site includes test data for use in demonstratingnumerical problems, code for applying the original methodsdescribed in the book, and an online bibliography of Web resourcesfor the statistical computation Designed as an independent research tool, a professionalreference, or a classroom supplement, the book presents awell-thought-out treatment of a complex and multifaceted field.

Elements of Computational Statistics

Elements of Computational Statistics
Author: James E. Gentle
Publisher: Springer Science & Business Media
Total Pages: 427
Release: 2006-04-18
Genre: Computers
ISBN: 0387216111

Download Elements of Computational Statistics Book in PDF, Epub and Kindle

Will provide a more elementary introduction to these topics than other books available; Gentle is the author of two other Springer books

Numerical Analysis Using R

Numerical Analysis Using R
Author: Graham W. Griffiths
Publisher: Cambridge University Press
Total Pages: 637
Release: 2016-04-26
Genre: Mathematics
ISBN: 131665415X

Download Numerical Analysis Using R Book in PDF, Epub and Kindle

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.

Elementary Numerical Analysis (3Rd Ed.)

Elementary Numerical Analysis (3Rd Ed.)
Author: Atkinson
Publisher: John Wiley & Sons
Total Pages: 580
Release: 2009-07
Genre:
ISBN: 9788126508020

Download Elementary Numerical Analysis (3Rd Ed.) Book in PDF, Epub and Kindle

Offering a clear, precise, and accessible presentation, complete with MATLAB programs, this new Third Edition of Elementary Numerical Analysis gives students the support they need to master basic numerical analysis and scientific computing. Now updated and revised, this significant revision features reorganized and rewritten content, as well as some new additional examples and problems.The text introduces core areas of numerical analysis and scientific computing along with basic themes of numerical analysis such as the approximation of problems by simpler methods, the construction of algorithms, iteration methods, error analysis, stability, asymptotic error formulas, and the effects of machine arithmetic.· Taylor Polynomials · Error and Computer Arithmetic · Rootfinding · Interpolation and Approximation · Numerical Integration and Differentiation · Solution of Systems of Linear Equations · Numerical Linear Algebra: Advanced Topics · Ordinary Differential Equations · Finite Difference Method for PDEs