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Modeling with data : tools and techniques for scientific computing /
Modeling with Data fully explains how to execute computationally intensive analyses on very large data sets, showing readers how to determine the best methods for solving a variety of different problems, how to create and debug statistical models, and how to run an analysis and evaluate the results....
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Princeton, N.J. :
Princeton University Press,
©2009.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Klemens, Ben. | |
| 245 | 1 | 0 | |a Modeling with data : |b tools and techniques for scientific computing / |c Ben Klemens. |
| 260 | |a Princeton, N.J. : |b Princeton University Press, |c ©2009. | ||
| 300 | |a 1 online resource (xiii, 454 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 504 | |a Includes bibliographical references (pages 435-442) and index. | ||
| 520 | |a Modeling with Data fully explains how to execute computationally intensive analyses on very large data sets, showing readers how to determine the best methods for solving a variety of different problems, how to create and debug statistical models, and how to run an analysis and evaluate the results. Ben Klemens introduces a set of open and unlimited tools, and uses them to demonstrate data management, analysis, and simulation techniques essential for dealing with large data sets and computationally intensive procedures. He then demonstrates how to easily apply these tools to the many threads o. | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Preliminaries; CONTENTS; Chapter 1. Statistics in the modern day; Chapter 2. C; Chapter 3. Databases; Chapter 4. Matrices and models; Chapter 5. Graphics; Chapter 6. More coding tools; Chapter 7. Distributions for description; Chapter 8. Linear projections; Chapter 9. Hypothesis testing with the CLT; Chapter 10. Maximum likelihood estimation; Chapter 11. Monte Carlo; Appendix A: Environments and makefiles; Appendix B: Text processing; Appendix C: Glossary; Bibliography; Index. | |
| 590 | |a JSTOR |b Books at JSTOR All Purchased | ||
| 590 | |a JSTOR |b Books at JSTOR Evidence Based Acquisitions | ||
| 590 | |a JSTOR |b Books at JSTOR Demand Driven Acquisitions (DDA) | ||
| 650 | 0 | |a Mathematical statistics. | |
| 650 | 0 | |a Mathematical models. | |
| 650 | 6 | |a Modèles mathématiques. | |
| 650 | 7 | |a mathematical models. |2 aat | |
| 650 | 7 | |a COMPUTERS |x Data Modeling & Design. |2 bisacsh | |
| 650 | 7 | |a Mathematical models. |2 fast |0 (OCoLC)fst01012085 | |
| 650 | 7 | |a Mathematical statistics. |2 fast |0 (OCoLC)fst01012127 | |
| 776 | 0 | 8 | |i Print version: |a Klemens, Ben. |t Modeling with data. |d Princeton, N.J. : Princeton University Press, ©2009 |w (DLC) 2008028341 |
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