{"product_id":"modelling-spatial-and-spatial-temporal-data-a-bayesian-approach-9781032175003","title":"Modelling Spatial and Spatial-Temporal Data: A Bayesian Approach","description":"\u003cp\u003e • Author(s): Robert P. Haining\u003cbr\u003e • Publisher: Taylor \u0026amp; Francis\u003cbr\u003e • Publisher Imprint: CRC Press\u003cbr\u003e • BISAC: Probability \u0026amp; Statistics - Bayesian Analysis\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eModelling Spatial and Spatial-Temporal Data: A Bayesian Approach\u003c\/strong\u003e is aimed at statisticians and quantitative social, economic and public health students and researchers who work with small-area spatial and spatial-temporal data. It assumes a grounding in statistical theory up to the standard linear regression model. The book compares both hierarchical and spatial econometric modelling, providing both a reference and a teaching text with exercises in each chapter. The book provides a fully Bayesian, self-contained, treatment of the underlying statistical theory, with chapters dedicated to substantive applications. The book includes WinBUGS code and R code and all datasets are available online.\u003c\/p\u003e\u003cp\u003ePart I covers fundamental issues arising when modelling spatial and spatial-temporal data. Part II focuses on modelling cross-sectional spatial data and begins by describing exploratory methods that help guide the modelling process. There are then two theoretical chapters on Bayesian models and a chapter of applications. Two chapters follow on spatial econometric modelling, one describing different models, the other substantive applications. Part III discusses modelling spatial-temporal data, first introducing models for time series data. Exploratory methods for detecting different types of space-time interaction are presented, followed by two chapters on the theory of space-time separable (without space-time interaction) and inseparable (with space-time interaction) models. An applications chapter includes: the evaluation of a policy intervention; analysing the temporal dynamics of crime hotspots; chronic disease surveillance; and testing for evidence of spatial spillovers in the spread of an infectious disease. A final chapter suggests some future directions and challenges.\u003c\/p\u003e","brand":"Taylor \u0026 Francis","offers":[{"title":"Paperback","offer_id":45241367822487,"sku":"9781032175003","price":4273.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9781032175003.webp?v=1769228507","url":"https:\/\/atlanticbooks.com\/products\/modelling-spatial-and-spatial-temporal-data-a-bayesian-approach-9781032175003","provider":"Atlantic Books","version":"1.0","type":"link"}