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Applied Probability Models with Optimization Applications (Dover Books on Mathematics)
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HKD 167
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A clarity of style and a conciseness of treatment which students will find most welcome. The material is valuable and well organized … an excellent introduction to applied probability. — Journal of the American Statistical Association.
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產品詳情
| Item Weight | 1 lbs (450 grams) |
Who Should Buy?
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Graduate Students
Ideal for graduate-level students studying applied probability and optimization in mathematics and engineering fields.
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Professionals
Suitable for professionals working in domains requiring quantitative analysis, such as finance, logistics, and operations research.
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Researchers
Beneficial for researchers focused on developing models that incorporate probability and optimization methodologies in their work.
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Casual Readers
Not suitable for casual readers without a strong mathematical background or interest in advanced probability topics.
產品敘述
Applied Probability Models with Optimization Applications (Dover Books on Mathematics)
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Probability & Statistics Editorial Review
The Applied Probability Models with Optimization Applications Dover textbook is generally well-received by those with a solid foundation in statistics and probability. The book is regarded as a useful reference for graduate students in mathematics or statistics and is deemed suitable for a stochastic optimization course. It is suggested as a next step after introductory level statistics and probability courses. Some readers feel that the book focuses heavily on examples from finance and economics, wishing for more diverse applications in the sciences. It has also been mentioned that the book delves into the practical applications of Markov Decision Processes. Despite this, a few readers express a need for more detailed information on the subject. Overall, the price is Considered affordable for the content provided. **
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優點
- Useful reference for graduate math or stat students
- Suitable for stochastic optimization course
- Affordable price
- Great resource for building probability models
- Provides practical examples and applications of Markov Decision Processes
缺點
- Heavy focus on finance and economics examples
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HKD 167
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特色和優勢
- Concise introduction to stochastic processes in applied probability
- Emphasis on optimization models and decision processes
- Covers Poisson processes, renewal theory, Markov chains, inventory theory, and more
- Includes section of useful problems and relevant references for each chapter
- Largely self-contained text suitable for advanced undergraduate or beginning postgraduate level
- Suited for a one-year course in applied probability
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