(Redirected from Numerical Recipes in C)
Author | William H. Press, Saul A. Teukolsky, William T. Vetterling and Brian P. Flannery |
---|---|
Language | English |
Discipline | Numerical analysis |
Publisher | Cambridge University Press |
Website | numerical.recipes |
All other legacy Numerical Recipes code from the First and Second editions, in languages including Fortran, Basic, Pascal, Modula 2, and Lisp is included in the Numerical Recipes All Languages Code Download, see order form. This code is all also on the Numerical Recipes Source-Code CDROM Third Edition, available here from Amazon.com.
Numerical Recipes is the generic title of a series of books on algorithms and numerical analysis by William H. Press, Saul A. Teukolsky, William T. Vetterling and Brian P. Flannery. In various editions, the books have been in print since 1986. The most recent edition was published in 2007. In 2015 Numerical Recipes sold its historic two-letter domain name nr.com[1] and became
numerical.recipes
instead.Overview[edit]
The Numerical Recipes books cover a range of topics that include both classical numerical analysis (interpolation, integration, linear algebra, differential equations, and so on), signal processing (Fourier methods, filtering), statistical treatment of data, and a few topics in machine learning (hidden Markov model, support vector machines). The writing style is accessible and has an informal tone. The emphasis is on understanding the underlying basics of techniques, not on the refinements that may, in practice, be needed to achieve optimal performance and reliability. Few results are proved with any degree of rigor, although the ideas behind proofs are often sketched, and references are given. Importantly, virtually all methods that are discussed are also implemented in a programming language, with the code printed in the book. Each version is keyed to a specific language.
According to the publisher, Cambridge University Press, the Numerical Recipes books are historically the all-time best-selling books on scientific programming methods. In recent years, Numerical Recipes books have been cited in the scientific literature more than 3000 times per year according to ISI Web of Knowledge (e.g., 3962 times in the year 2008).[2] And as of the end of 2017, the book had over 44000 citations on Google Scholar.[3]
History[edit]
The first publication was in 1986 with the title,”Numerical Recipes, The Art of Scientific Computing”, containing code in both Fortran and Pascal; an accompanying book, “Numerical Recipes Example Book (Pascal) was first published in 1985. (A preface note in “Examples' mentions that the main book was also published in 1985, but the official note in that book says 1986.) Supplemental editions followed with code in Pascal, BASIC, and C. Numerical Recipes took, from the start, an opinionated editorial position at odds with the conventional wisdom of the numerical analysis community:
“ | If there is a single dominant theme in this book, it is that practical methods of numerical computation can be simultaneously efficient, clever, and — important — clear. The alternative viewpoint, that efficient computational methods must necessarily be so arcane and complex as to be useful only in 'black box' form, we firmly reject.[4] | ” |
However, as it turned out, the 1980s were fertile years for the 'black box' side, yielding important libraries such as BLAS and LAPACK, and integrated environments like MATLAB and Mathematica. By the early 1990s, when Second Edition versions of Numerical Recipes (with code in C, Fortran-77, and Fortran-90) were published, it was clear that the constituency for Numerical Recipes was by no means the majority of scientists doing computation, but only that slice that lived between the more mathematical numerical analysts and the larger community using integrated environments. The Second Edition versions occupied a stable role in this niche environment.[5]
By the mid-2000s, the practice of scientific computing had been radically altered by the mature Internet and Web. Recognizing that their Numerical Recipes books were increasingly valued more for their explanatory text than for their code examples, the authors significantly expanded the scope of the book, and significantly rewrote a large part of the text. They continued to include code, still printed in the book, now in C++, for every method discussed.[6] The Third Edition was also released as an electronic book,[7] eventually made available on the Web for free (with limited page views) or by paid or institutional subscription (with unlimited page views).
Criticism[edit]
Numerical Recipes is a single volume that covers very broad range of algorithms. Unfortunately that format skewed the choice of algorithms towards simpler and shorter early algorithms which were not as accurate, efficient or stable as later more complex algorithms.[8][9][10][11] The first edition had also some minor bugs, which were fixed in later editions; however according to the authors for years they were encountering on the internet rumors that Numerical Recipes is 'full of bugs'. They attributed this to people using outdated versions of the code, bugs in other parts of the code and misuse of routines which require some understanding to use correctly.[12]
The code listings are copyrighted and commercially licensed by the Numerical Recipes authors.[13] However, Numerical Recipes includes the following statement regarding copyrights on computer programs:
Copyright does not protect ideas, but only the expression of those ideas in a particular form. In the case of a computer program, the ideas consist of the program's methodology and algorithm, including the necessary sequence of steps adopted by the programmer. The expression of those ideas is the program source code.. If you analyze the ideas contained in a program, and then express those ideas in your own completely different implementation, then that new program implementation belongs to you.[7]
One early motivation for the GNU Scientific Library was that a free library was needed as a substitute for Numerical Recipes.[14]
Another line of criticism centers on the coding style of the books, which strike some modern readers as 'Fortran-ish', though written in contemporary, object-oriented C++[14]. The authors have defended their very terse coding style as necessary to the format of the book because of space limitations and for readability.[5]
Titles in the series (partial list)[edit]
The books differ by edition (1st, 2nd, and 3rd) and by the computer language in which the code is given.
- Numerical Recipes. The Art of Scientific Computing, 1st Edition, 1986, ISBN0-521-30811-9. (FORTRAN and Pascal)
- Numerical Recipes. The Art of Scientific Computing, 3rd Edition, 2007, ISBN0-521-88068-8. (C++ code)
- Numerical Recipes in C. The Art of Scientific Computing, 2nd Edition, 1992, ISBN0-521-43108-5.
- Numerical Recipes in Fortran. The Art of Scientific Computing, 2nd Edition, 1992, ISBN0-521-43064-X.
- Numerical Recipes in Fortran 90. The Art of Parallel Scientific Computing, 2nd Edition, 1996, ISBN0-521-57439-0.
- Numerical Recipes in Pascal. The Art of Scientific Computing, 1st Edition, 1989, ISBN0-521-37516-9.
The books are published by Cambridge University Press.
References[edit]
- ^'Two letter domain NR.com sold : Rebrands to Numerical.Recipes'. 14 October 2015.
- ^Thomson Reuters, Web of Knowledge, Cited Reference Search.
- ^[1], Google Scholar
- ^Press, William H.; Teukolsky, Saul A.; Vetterling, William T.; Flannery, Brian P. (1986). 'Preface'. Numerical Recipes: The Art of Scientific Computing. New York: Cambridge University Press. p. xi. ISBN0-521-30811-9.
- ^ abPress, William H.; and Teukolsky, Saul A.; 'Numerical Recipes: Does This Paradigm Have a Future?,' Computers in Physics, 11, 416 (1997). Preprint.
- ^Press, William H.; Teukolsky, Saul A.; Vetterling, William T.; Flannery, Brian P. (2007). 'Preface to the Third Edition'. Numerical Recipes: The Art of Scientific Computing (3rd ed.). New York: Cambridge University Press. p. xi. ISBN978-0-521-88068-8.
- ^ abPress, William H.; Teukolsky, Saul A.; Vetterling, William T.; Flannery, Brian P. (2007). Numerical Recipes: The Art of Scientific Computing (3rd ed.). New York: Cambridge University Press. ISBN978-0-521-88068-8.
- ^Harrop, Jon (13 March 2011). 'The Flying Frog Blog: Alternatives to Numerical Recipes'. The Flying Frog Blog. Retrieved 28 January 2019.
- ^'Reviews: Numerical Recipes'. www.quut.com. Retrieved 28 January 2019.clone URL
- ^Van Snyder, W. 'Why not use Numerical Recipes?'. www.uwyo.edu. Retrieved 28 January 2019.clone URL
- ^'Alternatives to Numerical Recipes'. Archived from the original on 18 Jan 2016.
- ^'Numerical Recipes Distressing Rumors'. numerical.recipes. Retrieved 28 January 2019.
- ^Numerical Recipes Web site, Numerical Recipes Code
- ^ abGalassi, Mark; Theiler, James; Gough, Brian. 'GNU Scientific Library -- Design document'. GNU Operating System. GNU.org. Retrieved January 5, 2019.
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External links[edit]
- Current electronic edition of Numerical Recipes (limited free page views).
- Numerical Recipes at Google Books
- Older versions of Numerical Recipes available electronically (links to C, Fortran 77, and Fortran 90 versions in various formats, plus other hosted books)
- Norman Gray, A balanced discussion of NR and its critics
- 'Alternatives to Numerical Recipes'. Archived from the original on 18 Jan 2016.
Retrieved from 'https://en.wikipedia.org/w/index.php?title=Numerical_Recipes&oldid=943776976'
Download Free Numerical Recipes 3rd Edition The Art Of Scientific Computing Book in PDF and EPUB Free Download. You can read online Numerical Recipes 3rd Edition The Art Of Scientific Computing and write the review.
The essential text and reference for modern scientific computing now also covers computational geometry, classification and inference, and much more.
Numerical Recipes In C++ Code
This book/CD bundle of the greatly expanded third edition of Numerical Recipes now has wider coverage than ever before, many new, expanded and updated sections, and two completely new chapters. Co-authored by four leading scientists from academia and industry, Numerical Recipes starts with basic mathematics and computer science and proceeds to complete, working routines. The informal, easy-to-read style that made earlier editions so popular is kept throughout. Highlights of the new material include: a new chapter on classification and inference, Gaussian mixture models, HMMs, hierarchical clustering, and SVMs; a new chapter on computational geometry, covering KD trees, quad- and octrees, Delaunay triangulation, and algorithms for lines, polygons, triangles, and spheres; interior point methods for linear programming; MCMC; an expanded treatment of ODEs with completely new routines; and many new statistical distributions. For support or further licence information please visit www.nr.com.
The essential text and reference for modern scientific computing now also covers computational geometry, classification and inference, and much more.
The essential text and reference for modern scientific computing now also covers computational geometry, classification and inference, and much more.
Implementing Models of Financial Derivatives is a comprehensive treatment of advanced implementation techniques in VBA for models of financial derivatives. Aimed at readers who are already familiar with the basics of VBA it emphasizes a fully object oriented approach to valuation applications, chiefly in the context of Monte Carlo simulation but also more broadly for lattice and PDE methods. Its unique approach to valuation, emphasizing effective implementation from both the numerical and the computational perspectives makes it an invaluable resource. The book comes with a library of almost a hundred Excel spreadsheets containing implementations of all the methods and models it investigates, including a large number of useful utility procedures. Exercises structured around four application streams supplement the exposition in each chapter, taking the reader from basic procedural level programming up to high level object oriented implementations. Written in eight parts, parts 1-4 emphasize application design in VBA, focused around the development of a plain Monte Carlo application. Part 5 assesses the performance of VBA for this application, and the final 3 emphasize the implementation of a fast and accurate Monte Carlo method for option valuation. Key topics include: ?Fully polymorphic factories in VBA; ?Polymorphic input and output using the TextStream and FileSystemObject objects; ?Valuing a book of options; ?Detailed assessment of the performance of VBA data structures; ?Theory, implementation, and comparison of the main Monte Carlo variance reduction methods; ?Assessment of discretization methods and their application to option valuation in models like CIR and Heston; ?Fast valuation of Bermudan options by Monte Carlo. Fundamental theory and implementations of lattice and PDE methods are presented in appendices and developed through the book in the exercise streams. Spanning the two worlds of academic theory and industrial practice, this book is not only suitable as a classroom text in VBA, in simulation methods, and as an introduction to object oriented design, it is also a reference for model implementers and quants working alongside derivatives groups. Its implementations are a valuable resource for students, teachers and developers alike. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.
Presents inference and simulation of stochastic process in the field of model calibration for financial times series modelled by continuous time processes and numerical option pricing. Introduces the bases of probability theory and goes on to explain how to model financial times series with continuous models, how to calibrate them from discrete data and further covers option pricing with one or more underlying assets based on these models. Analysis and implementation of models goes beyond the standard Black and Scholes framework and includes Markov switching models, Lévy models and other models with jumps (e.g. the telegraph process); Topics other than option pricing include: volatility and covariation estimation, change point analysis, asymptotic expansion and classification of financial time series from a statistical viewpoint. The book features problems with solutions and examples. All the examples and R code are available as an additional R package, therefore all the examples can be reproduced.
Determining the intrinsic microwave properties of materials is important for a variety of applications ranging from antenna and electronic circuit design to remote sensing to electromagnetic interference mitigation. A number of methods exist for characterizing intrinsic properties of materials at microwave frequencies, including transmission lines, resonant cavities, and impedance analysis. The use of free-space measurement methods has become commonplace among microwave material characterization laboratories due to its ease of use and reasonable accuracy. While some free-space facilities exist that can characterize down to 500 MHz, the method is most useful for characterizing materials from 2 GHz through millimeter waves. This book is designed to acquaint engineers and scientists with the theory and practice of using microwave focused beam systems for free-space characterization of materials.