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Introduction to scientific programming and simulation using R / Owen Jones, Robert Maillardet and Andrew Robinson.

By: Contributor(s): Material type: TextTextSeries: Chapman & Hall/CRC the R seriesPublication details: Boca Raton : CRC Press, c2014.Edition: 2nd edDescription: xxiv, 582 p. : illustrations ; 24 cmISBN:
  • 9781466569997
Other title:
  • Scientific programming and simulation using R
Subject(s): DDC classification:
  • 502.8553  23 J78
Contents:
1. Setting up-- 2. R as a calculating environment-- 3. Basic programming-- 4. I/O: Input and output-- 5. Programming with functions-- 6. Sophisticated data structures-- 7. Better graphics-- 8. Pointers to further programming techniques-- 9. Numerical accuracy and program efficiency-- 10. Root-finding-- 11. Numerical integration-- 12. Optimization-- 13. Systems of ordinary differential equations-- 14. Probability-- 15. Random variables-- 16. Discrete random variables-- 17. Continuous random variables-- 18. Parameter estimation-- 19. Markov chains-- 20. Simulation-- 21. Monte Carlo integration-- 22. Variance reduction-- 23. Case studies-- 24. Student projects-- Glossary of R commands-- Programs and functions developed in the text-- Index.
Summary: This second edition continues to introduce scientific programming and stochastic modelling in a clear, practical, and thorough way. Readers learn programming by experimenting with the provided R code and data.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books ISI Library, Kolkata 502.8553 J78 (Browse shelf(Opens below)) Available 136064
Total holds: 0

Includes index.

1. Setting up--
2. R as a calculating environment--
3. Basic programming--
4. I/O: Input and output--
5. Programming with functions--
6. Sophisticated data structures--
7. Better graphics--
8. Pointers to further programming techniques--
9. Numerical accuracy and program efficiency--
10. Root-finding--
11. Numerical integration--
12. Optimization--
13. Systems of ordinary differential equations--
14. Probability--
15. Random variables--
16. Discrete random variables--
17. Continuous random variables--
18. Parameter estimation--
19. Markov chains--
20. Simulation--
21. Monte Carlo integration--
22. Variance reduction--
23. Case studies--
24. Student projects--
Glossary of R commands--
Programs and functions developed in the text--
Index.

This second edition continues to introduce scientific programming and stochastic modelling in a clear, practical, and thorough way. Readers learn programming by experimenting with the provided R code and data.

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