Information-theoretic methods for estimating complicated probability distributions
There have been constant efforts to find appropriate methods to determine complicated distributions based on random samples, but this topic has never been systematically discussed in detail in a book or monograph. The present book is intended to fill the gap and documents the latest research in this...
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| Format: | eBook |
| Language: | English |
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Amsterdam
Elsevier
2006, 2006
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| Edition: | 1st ed |
| Series: | Mathematics in science and engineering
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| Online Access: | |
| Collection: | Elsevier eBook collection Mathematics - Collection details see MPG.ReNa |
Table of Contents:
- Randomness and probability
- Inference and statistics
- Random numbers and their applications
- Approximation and B-spline function
- Disorder, entropy and entropy estimation
- Estimation of 1-D complicated distributions based on large samples
- Estimation of 2-D complicated distributions based on large samples
- Estimation of 1-D complicated distribution based on small samples
- Estimation of 2-D complicated distribution based on small samples
- Estimation of the membership function
- Estimation of distributions by use of the maximum entropy method
- Code specifications
- Includes bibliographical references (pages 289-293) and index