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物品 #:
87448306
Advanced Spatial Modeling With Stochastic Partial Differential Equations Us...
物品 #:
87448306
HKD 795
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現在訂購，約可在下列時間收貨： 星期五, 十一月 06
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Modeling Spatial And Spatio-Temporal Continuous Processes Is An Important And Challenging Problem In Spatial Statistics.
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What Stands Out
Cutting-edge Modeling
Utilizes advanced stochastic partial differential equations, offering highly accurate representations of complex spatial phenomena, allowing researchers to tackle challenging mathematical and scientific problems with confidence and precision.
Comprehensive Resource
Serves as a complete guide with in-depth explanations, examples, and applications, making it accessible for both novice and experienced researchers in understanding and applying advanced spatial modeling techniques.
Practical Applications
Addresses real-world problems across various fields, such as environmental science and finance, ensuring invaluable insights and solutions through sophisticated modeling approaches and robust analytical frameworks.
產品詳情
| Book Title | Advanced Spatial Modeling With Stochastic Partial Differenti... |
| ISBN | 9780367570644 |
| Subject Area | Mathematics, Computers |
| Publication Name | Advanced Spatial Modeling with Stochastic Partial Differential Equations Using Rand Inla |
| Publisher | CRC Press LLC |
| Item Length | 9.2 in (23.37 cm) |
| Subject | Programming Languages / General, Differential Equations / General, Probability & Statistics / Stochastic Processes, Probability & Statistics / General, General, Transformations |
| Publication Year | 2020 |
| Type | Textbook |
| Format | Trade Paperback |
| Language | English |
| Author | Elias Krainski, Haakon Bakka, Virgilio Gu00f3mez-Rubio, Amanda Lenzi, Daniela Castro-Camilo |
| Item Weight | 14.8 Oz (419.58 grams) |
| Item Width | 6.1 in (15.49 cm) |
| Number of Pages | 284 Pages |
Who Should Buy?
-
Research Scientists
Ideal for scientists needing advanced modeling techniques for spatial data involving uncertainties in fields like environmental science.
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Data Analysts
Beneficial for analysts exploring spatial datasets who require sophisticated mathematical tools for accurate predictions and insights.
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Graduate Students
Perfect for graduate students focusing on advanced mathematics or modeling, helping them understand complex spatial and stochastic concepts.
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Casual Users
Not suitable for casual users who seek simple models without the need for in-depth statistical understanding or software expertise.
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編輯評論
Advanced Spatial Modeling With Stochastic Partial Differential Equations Using Rand Inla is a meticulous exploration of advanced mathematical concepts written by renowned authors Elias Krainski, Haakon Bakka, Virgilio Gómez-Rubio, Amanda Lenzi, and Daniela Castro-Camilo. This textbook delves into subjects such as programming languages, differential equations, and stochastic processes, providing a comprehensive resource for both students and professionals in the fields of mathematics and computer science. The trade paperback format is practical for study, while the book's 284 pages are filled with essential knowledge that enhances understanding of spatial modeling techniques. This resource is particularly valuable for those looking to apply these mathematical principles. Readers have praised its clarity and in-depth approach to complex topics.
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優點
- Clear explanations of complex mathematical concepts
- Practical applications in programming and statistics
- Authoritative insights from multiple experts
- Comprehensive resource for mathematics and computing
- User-friendly trade paperback format
缺點
- Lengthy chapters may require additional time to digest
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HKD 795
現在訂購，約可在下列時間收貨： 星期五, 十一月 06
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特色和優勢
- Comprehensive guide on Spatial Modeling with SPDEs.
- Utilizes R and INLA for advanced statistical analysis.
- Includes real-world applications across various fields.
- Written by leading experts in Spatial Statistics.
- All examples are reproducible with provided R code and datasets.
- Ideal resource for graduate and PhD students.
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