{"product_id":"bayesian-applications-in-environmental-and-song-s-qian-9781138497399","title":"Bayesian Applications in Environmental and Ecological Studies with R and Stan","description":"\u003cp\u003eModern ecological and environmental sciences are dominated by observational data. As a result, traditional statistical training often leaves scientists ill-prepared for the data analysis tasks they encounter in their work. Bayesian methods provide a more robust and flexible tool for data analysis, as they enable information from different sources to be brought into the modelling process. \u003cstrong\u003eBayesian Applications in Evnironmental and Ecological Studies with R and Stan\u003c\/strong\u003e provides a Bayesian framework for model formulation, parameter estimation, and model evaluation in the context of analyzing environmental and ecological data.\u003c\/p\u003e \u003cp\u003e\u003cstrong\u003eFeatures: \u003c\/strong\u003e\u003c\/p\u003e \u003cul\u003e \u003cli\u003eAn accessible overview of Bayesian methods in environmental and ecological studies\u003c\/li\u003e \u003cli\u003eEmphasizes the hypothetical deductive process, particularly model formulation\u003c\/li\u003e \u003cli\u003eNecessary background material on Bayesian inference and Monte Carlo simulation\u003c\/li\u003e \u003cli\u003eDetailed case studies, covering water quality monitoring and assessment, ecosystem response to urbanization, fisheries ecology, and more\u003c\/li\u003e \u003cli\u003eAdvanced chapter on Bayesian applications, including Bayesian networks and a change point model\u003c\/li\u003e \u003cli\u003eComplete code for all examples, along with the data used in the book, are available via GitHub\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003eThe book is primarily aimed at graduate students and researchers in the environmental and ecological sciences, as well as environmental management professionals. This is a group of people representing diverse subject matter fields, who could benefit from the potential power and flexibility of Bayesian methods.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAuthor:\u003c\/b\u003e Song S. Qian, Mark R. Dufour, Ibrahim Alameddine\u003cbr\u003e\u003cb\u003eISBN-10:\u003c\/b\u003e 1138497398\u003cbr\u003e\u003cb\u003eISBN-13:\u003c\/b\u003e 9781138497399\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e CRC Press\u003cbr\u003e\u003cb\u003eLanguage:\u003c\/b\u003e English\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 08\/29\/2022\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 395\u003cbr\u003e\u003cb\u003eFormat:\u003c\/b\u003e Hardcover\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 1.67lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 9.21h x 6.14w x 0.94d\u003c\/p\u003e","brand":"Song S. Qian","offers":[{"title":"Hardcover","offer_id":44071327301887,"sku":"9781138497399","price":130.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0662\/2982\/9887\/files\/img_f3e47850-bd51-4dd1-9845-2d0be4add5cb.jpg?v=1685435454","url":"https:\/\/www.whiterainbookhouse.com\/products\/bayesian-applications-in-environmental-and-song-s-qian-9781138497399","provider":"WR Book House","version":"1.0","type":"link"}