This book is an effort to integrate statistical theory with practical implementation. While emphasizing the fundamental concepts of time series analysis, it also provides step-by-step illustrations using Python programming. The aim is to make the subject both conceptually clear and practically relevant for students, researchers, and practitioners. Designed primarily for undergraduate and postgraduate students of statistics, mathematics, economics, and computer science, this book also serves as a reference for faculty members, professionals, and data analysts who seek to apply forecasting techniques in their respective fields. Topics such as stationarity, ARIMA models, exponential smoothing, decomposition, and advanced machine learning approaches are discussed systematically, supported by examples and applications.
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Paperback. Condición: new. Paperback. This book is an effort to integrate statistical theory with practical implementation. While emphasizing the fundamental concepts of time series analysis, it also provides step-by-step illustrations using Python programming. The aim is to make the subject both conceptually clear and practically relevant for students, researchers, and practitioners. Designed primarily for undergraduate and postgraduate students of statistics, mathematics, economics, and computer science, this book also serves as a reference for faculty members, professionals, and data analysts who seek to apply forecasting techniques in their respective fields. Topics such as stationarity, ARIMA models, exponential smoothing, decomposition, and advanced machine learning approaches are discussed systematically, supported by examples and applications. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9786630008944
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Taschenbuch. Condición: Neu. Time Series Forecasting and Advanced Predictive Models | Bridging Classical Statistics and Modern AI | Jhansi Rani Boina (u. a.) | Taschenbuch | Englisch | 2026 | Scholars' Press | EAN 9786630008944 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. Nº de ref. del artículo: 135723635
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware 176 pp. Englisch. Nº de ref. del artículo: 9786630008944
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Paperback. Condición: new. Paperback. This book is an effort to integrate statistical theory with practical implementation. While emphasizing the fundamental concepts of time series analysis, it also provides step-by-step illustrations using Python programming. The aim is to make the subject both conceptually clear and practically relevant for students, researchers, and practitioners. Designed primarily for undergraduate and postgraduate students of statistics, mathematics, economics, and computer science, this book also serves as a reference for faculty members, professionals, and data analysts who seek to apply forecasting techniques in their respective fields. Topics such as stationarity, ARIMA models, exponential smoothing, decomposition, and advanced machine learning approaches are discussed systematically, supported by examples and applications. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9786630008944
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