Xing haipeng (28 Ergebnisse)

Paperback. Zustand: Very Good. 7. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

Zustand: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,700grams, ISBN:9781498795630.

Zustand: New. pp. 376 Illus.

Zustand: New.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New. In English.

paperback. Zustand: Gut. 376 Seiten; 9781441926685.3 Gewicht in Gramm: 1.

Zustand: NEW.

Taschenbuch. Zustand: Neu. Neuware - The field of time series analysis has undergone a remarkable transformation since the publication of the seventh edition of this book. While classical statistical models such as autoregressive integrated moving average (ARIMA), state-space models, and spectral methods remain essential, the rise of artificial intelligence (AI) has introduced groundbreaking approaches to modelling, forecasting, and generating time-dependent data. This eighth edition of The Analysis of Time Series: An Introduction with R reflects these advancements with the addition of two new chapters: Predictive AI for Time Series and Generative AI for Time Series. These chapters bridge the gap between traditional time series methods and cutting-edge AI techniques, offering readers a comprehensive and integrated perspective on the field.Features - Comprehensive coverage of classical time series models including ARIMA, state-space models, and spectral methods - Two new chapters on predictive and generative AI, introducing cutting-edge methods like transformers, variational autoencoders, and diffusion models - Practical examples and illustrations using R, demonstrating the application of both classical and AI-based approaches to real-world time series data - Emphasis on the integration of classical statistical rigor with the flexibility and scalability of AI methods - Clear explanations and intuitive insights, making advanced concepts accessible to a broad audience - Updated content reflecting the latest developments in time series analysis, with a focus on modern, high-dimensional, and nonlinear data challenges The Analysis of Time Series: An Introduction with R, Eighth Edition is designed for students, researchers, and practitioners in statistics, as well as in finance, economics, climate science, health, and engineering. It serves as both a foundational text for those new to time series analysis and a valuable resource for experienced analysts seeking to engage with the rapidly evolving landscape of predictive and generative AI. With its balance of theory, practical implementation, and real-world examples, the book is ideal for use in academic courses, professional training, and self-study.…

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The idea of writing this bookarosein 2000when the rst author wasassigned to teach the required course STATS 240 (Statistical Methods in Finance) in the new M. S. program in nancial mathematics at Stanford, which is an interdisciplinary program that aims to provide a master's-level education in applied mathematics, statistics, computing, nance, and economics. Students in the programhad di erent backgroundsin statistics. Some had only taken a basic course in statistical inference, while others had taken a broad spectrum of M. S. - and Ph. D. -level statistics courses. On the other hand, all of them had already taken required core courses in investment theory and derivative pricing, and STATS 240 was supposed to link the theory and pricing formulas to real-world data and pricing or investment strategies. Besides students in theprogram,thecoursealso attractedmanystudentsfromother departments in the university, further increasing the heterogeneity of students, as many of them had a strong background in mathematical and statistical modeling from the mathematical, physical, and engineering sciences but no previous experience in nance. To address the diversity in background but common strong interest in the subject and in a potential career as a 'quant' in the nancialindustry,thecoursematerialwascarefullychosennotonlytopresent basic statistical methods of importance to quantitative nance but also to summarize domain knowledge in nance and show how it can be combined with statistical modeling in nancial analysis and decision making. The course material evolved over the years, especially after the second author helped as the head TA during the years 2004 and 2005.…

Zustand: New. 2026. 8th Edition. paperback. . . . . . Books ship from the US and Ireland.

Zustand: New. In English.

Paperback. Zustand: Brand New. 8th edition. 416 pages. 9.18x6.12x9.21 inches. In Stock.

Zustand: New. Haipeng Xing is a professor in applied mathematics and statistics at the State University of New York, Stony Brook, USA, the author of three books and numerous research papers. His research interests include quantitative finance and risk managemen.

Zustand: New. In English.

Zustand: New. In English.

Paperback. Zustand: Brand New. 7th new edition. 416 pages. 9.25x6.00x1.00 inches. In Stock.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The idea of writing this bookarosein 2000when the rst author wasassigned to teach the required course STATS 240 (Statistical Methods in Finance) in the new M. S. program in nancial mathematics at Stanford, which is an interdisciplinary program that aims to provide a master's-level education in applied mathematics, statistics, computing, nance, and economics. Students in the programhad di erent backgroundsin statistics. Some had only taken a basic course in statistical inference, while others had taken a broad spectrum of M. S. - and Ph. D. -level statistics courses. On the other hand, all of them had already taken required core courses in investment theory and derivative pricing, and STATS 240 was supposed to link the theory and pricing formulas to real-world data and pricing or investment strategies. Besides students in theprogram,thecoursealso attractedmanystudentsfromother departments in the university, further increasing the heterogeneity of students, as many of them had a strong background in mathematical and statistical modeling from the mathematical, physical, and engineering sciences but no previous experience in nance. To address the diversity in background but common strong interest in the subject and in a potential career as a 'quant' in the nancialindustry,thecoursematerialwascarefullychosennotonlytopresent basic statistical methods of importance to quantitative nance but also to summarize domain knowledge in nance and show how it can be combined with statistical modeling in nancial analysis and decision making. The course material evolved over the years, especially after the second author helped as the head TA during the years 2004 and 2005.…

Hardcover. Zustand: Brand New. 1st edition. 350 pages. 6.14x1.24x9.21 inches. In Stock.

Zustand: gut. 2010. Statistical Models and Methods for Financial Markets (Springer Texts in Statistics) In englischer Sprache. pages.

Zustand: New.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New.

Zustand: New. Haipeng Xing is a professor in applied mathematics and statistics at the State University of New York, Stony Brook, USA, the author of three books and numerous research papers. His research interests include quantitative finance and risk managemen.

Zustand: New. In English.

Hardcover. Zustand: Brand New. 8th edition. 416 pages. 9.18x6.12x9.45 inches. In Stock.

Hardcover. Zustand: Brand New. 7th edition. 398 pages. 9.50x6.25x1.00 inches. In Stock.