Monte Carlo Statistical Methods by Christian P Robert
Until the advent of powerful and accessible computing methods, the experimenter was often confronted with a difficult choice. Either describe an accurate model of a phenomenon, which would usually preclude the computation of explicit answers, or choose a standard model which would allow this computation, but may not be a close representation of a realistic model. This dilemma is present in many branches of statistical applications, for example in electrical engineering, aeronautics, biology, networks, and astronomy. Markov chain Monte Carlo methods have been developed to provide realistic models.-
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A Modern Introduction to Probability and Statistics
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Introduction to Time Series and Forecasting
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Applied Multivariate Data Analysis
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Probability
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Introduction to Statistical Inference
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Prescriptions for Working Statisticians
| SKU | Unavailable |
| ISBN 13 | 9780387987071 |
| ISBN 10 | 038798707X |
| Title | Monte Carlo Statistical Methods |
| Author | Christian P Robert |
| Series | Springer Texts In Statistics |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Springer-Verlag New York Inc. |
| Year published | 1999-08-01 |
| Number of pages | 528 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |