{"product_id":"modeling-space-and-time-spatio-temporal-methods-for-epidemics-and-climate-forecasting-9798265229045","title":"Modeling Space and Time: Spatio-Temporal Methods for Epidemics and Climate Forecasting","description":"\u003cp\u003e • Author(s): Eliza Harper | Jonathan M. Reeves\u003cbr\u003e • Publisher: Independently Published\u003cbr\u003e • Publisher Imprint: Independently Published\u003cbr\u003e • BISAC: Data Processing\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eModeling Space and Time: Spatio-Temporal Methods for Epidemics and Climate Forecasting\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003eHow do we understand patterns that unfold across both space and time?\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003eThis comprehensive guide introduces the theory and practice of spatio-temporal modeling, offering readers the tools to analyze data that changes not only when events happen but also where they occur. With clear explanations and real-world applications, the book brings together methods from statistics, machine learning, and applied sciences.\u003c\/p\u003e\u003cp\u003eStarting with foundational concepts in spatial statistics and time series analysis, the text moves step by step into advanced models such as Gaussian processes, hierarchical frameworks, and Bayesian approaches. Modern machine learning techniques are also explored, showing how neural networks and ensemble methods can enhance forecasting in complex systems.\u003c\/p\u003e\u003cp\u003eApplications are given special attention. Readers will find detailed chapters on epidemic modeling, including both traditional compartmental frameworks and their spatial extensions, as well as in-depth treatment of climate science, from data sources and trend detection to forecasting with coupled ocean-atmosphere models.\u003c\/p\u003e\u003cp\u003eBy combining rigorous methods with accessible case studies, this book provides both the theoretical grounding and practical insight needed to approach spatio-temporal problems with confidence.This book is an essential resource for graduate students, researchers, and professionals in data science, epidemiology, environmental studies, and applied statistics who want to understand and forecast the dynamics of space and time.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eInside you will learn: \u003c\/b\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003e\u003cp\u003eCore methods in spatial statistics and time series analysis\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eHow to integrate space and time using covariance structures and stochastic processes\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eAdvanced modeling strategies including hierarchical and Bayesian techniques\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eMachine learning approaches for large and complex data\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eApplications in epidemiology, including epidemic forecasting and spatial disease spread\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eApplications in climate science, including trend detection and forecasting models\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eKey challenges such as big data scalability, uncertainty quantification, and ethical considerations\u003c\/p\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003c\/p\u003e","brand":"Independently Published","offers":[{"title":"Paperback","offer_id":47968030982295,"sku":"9798265229045","price":912.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9798265229045.webp?v=1782916527","url":"https:\/\/atlanticbooks.com\/products\/modeling-space-and-time-spatio-temporal-methods-for-epidemics-and-climate-forecasting-9798265229045","provider":"Atlantic Books","version":"1.0","type":"link"}