Xing haipeng (79 resultados)

Condición: acceptable. Fast Free Shipping â" A well-loved copy with text fully readable and cover pages intact. May display wear such as writing, highlighting, bends, folds or library marks. Still a complete and usable book.

Paperback. Condición: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.

Paperback. Condición: 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.

Condición: very_good. This book is in Very good condition. There may be a few flaws like shelf wear and some light wear.

Condición: 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.

Hardcover. Condición: USED BOOKS. USED BOOKS ! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.…

Hardcover. Condición: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.

Condición: New.

Condición: New.

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

Condición: New.

Hardcover. Condición: New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Paperback. Condición: New. 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.FeaturesComprehensive coverage of classical time series models including ARIMA, state-space models, and spectral methodsTwo new chapters on predictive and generative AI, introducing cutting-edge methods like transformers, variational autoencoders, and diffusion modelsPractical examples and illustrations using R, demonstrating the application of both classical and AI-based approaches to real-world time series dataEmphasis on the integration of classical statistical rigor with the flexibility and scalability of AI methodsClear explanations and intuitive insights, making advanced concepts accessible to a broad audienceUpdated content reflecting the latest developments in time series analysis, with a focus on modern, high-dimensional, and nonlinear data challengesThe 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.…

Condición: New.

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

Condición: New.

Condición: New. 2026. 8th Edition. paperback. . . . . .

Condición: As New. Unread book in perfect condition.

Condición: New.

Paperback. Condición: New. 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.FeaturesComprehensive coverage of classical time series models including ARIMA, state-space models, and spectral methodsTwo new chapters on predictive and generative AI, introducing cutting-edge methods like transformers, variational autoencoders, and diffusion modelsPractical examples and illustrations using R, demonstrating the application of both classical and AI-based approaches to real-world time series dataEmphasis on the integration of classical statistical rigor with the flexibility and scalability of AI methodsClear explanations and intuitive insights, making advanced concepts accessible to a broad audienceUpdated content reflecting the latest developments in time series analysis, with a focus on modern, high-dimensional, and nonlinear data challengesThe 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.…

Condición: New.

Condición: NEW.

Condición: As New. Unread book in perfect condition.

Condición: New.

Hardcover. Condición: Used; Very Good. **SHIPPED FROM UK** We believe you will be completely satisfied with our quick and reliable service. All orders are dispatched as swiftly as possible! Buy with confidence! Greener Books.

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

Condición: New. pp. 350 1st Edition.

Taschenbuch. Condición: 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.…

Condición: New. pp. 376.

Condición: New.