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Statistical Computing in C++ and R /
With the advancement of statistical methodology inextricably linked to the use of computers, new methodological ideas must be translated into usable code and then numerically evaluated relative to competing procedures. In response to this, Statistical Computing in C++ and R concentrates on the writi...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Chapman and Hall/CRC,
2011.
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| Edición: | 1st edition. |
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
| LEADER | 00000cam a22000007a 4500 | ||
|---|---|---|---|
| 001 | OR_on1162606799 | ||
| 003 | OCoLC | ||
| 005 | 20231017213018.0 | ||
| 006 | m o d | ||
| 007 | cr cnu|||||||| | ||
| 008 | 071114s2011 xx o 000 0 eng | ||
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| 020 | |z 9781466515376 | ||
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| 020 | |z 9781420066500 | ||
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| 020 | |z 142006651X | ||
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| 024 | 8 | |a 9781420066500 | |
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| 035 | |a (OCoLC)1162606799 | ||
| 050 | 4 | |a QA276.4 |b .E87 2011 | |
| 082 | 0 | 4 | |a 519.50285/5133 |
| 049 | |a UAMI | ||
| 100 | 1 | |a Eubank, Randall, |e author. | |
| 245 | 1 | 0 | |a Statistical Computing in C++ and R / |c Eubank, Randall. |
| 250 | |a 1st edition. | ||
| 264 | 1 | |b Chapman and Hall/CRC, |c 2011. | |
| 300 | |a 1 online resource (556 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file | ||
| 520 | |a With the advancement of statistical methodology inextricably linked to the use of computers, new methodological ideas must be translated into usable code and then numerically evaluated relative to competing procedures. In response to this, Statistical Computing in C++ and R concentrates on the writing of code rather than the development and study of numerical algorithms per se. The book discusses code development in C++ and R and the use of these symbiotic languages in unison. It emphasizes that each offers distinct features that, when used in tandem, can take code writing beyond what can be obtained from either language alone. The text begins with some basics of object-oriented languages, followed by a "boot-camp" on the use of C++ and R. The authors then discuss code development for the solution of specific computational problems that are relevant to statistics including optimization, numerical linear algebra, and random number generation. Later chapters introduce abstract data structures (ADTs) and parallel computing concepts. The appendices cover R and UNIX Shell programming. Features Includes numerous student exercises ranging from elementary to challenging Integrates both C++ and R for the solution of statistical computing problems Uses C++ code in R and R functions in C++ programs Provides downloadable programs, available from the authors' website The translation of a mathematical problem into its computational analog (or analogs) is a skill that must be learned, like any other, by actively solving relevant problems. The text reveals the basic principles of algorithmic thinking essential to the modern statistician as well as the fundamental skill of communicating with a computer through the use of the computer languages C++ and R. The book lays the foundation for original code development in a research environment | ||
| 542 | |f Copyright © Chapman and Hall/CRC 2011 |g 2011 | ||
| 550 | |a Made available through: Safari, an O'Reilly Media Company. | ||
| 588 | |a Online resource; Title from title page (viewed December 1, 2011) | ||
| 505 | 0 | |a Front Cover; Dedication; Preface; Contents; List of Algorithms; 1. Introduction; 2. Computer representation of numbers; 3. A sketch of C++; 4. Generation of pseudo-random numbers; 5. Programming in R; 6. Creating classes and methods in R; 7. Numerical linear algebra; 8. Numerical optimization; 9. Abstract data structures; 10. Data structures in C++; 11. Parallel computing in C++ and R; A. An introduction to Unix; B. An introduction to R; C. C++ library extensions (TR1); D. The Matrix and Vector classes; E. The ranGen class; References | |
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Statistics |x Data processing. | |
| 650 | 0 | |a R (Computer program language) | |
| 650 | 0 | |a C++ (Computer program language) | |
| 650 | 6 | |a Statistique |x Informatique. | |
| 650 | 6 | |a R (Langage de programmation) | |
| 650 | 6 | |a C++ (Langage de programmation) | |
| 650 | 7 | |a C++ (Computer program language) |2 fast | |
| 650 | 7 | |a R (Computer program language) |2 fast | |
| 650 | 7 | |a Statistics |x Data processing |2 fast | |
| 700 | 1 | |a Kupresanin, Ana, |e author. | |
| 710 | 2 | |a Safari, an O'Reilly Media Company. | |
| 856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9781420066500/?ar |z Texto completo (Requiere registro previo con correo institucional) |
| 936 | |a BATCHLOAD | ||
| 994 | |a 92 |b IZTAP | ||