Numerical Analysis for Statisticians

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Focusing on the intersection of numerical analysis and statistics, this book provides a comprehensive guide for students and professionals alike. It covers essential topics such as numerical stability, computational complexity, and mathematical modeling, with an emphasis on crafting software and understanding various numerical methods. The second edition features extensive updates, including a rewritten optimization section, new chapters on advanced algorithms, and enhanced discussions on techniques like the bootstrap and hidden Markov chains. It serves as a valuable resource for both graduate and undergraduate courses in computational statistics.