Titlebook: Entropy Measures for Environmental Data; Description, Samplin Linda Altieri,Daniela Cocchi Book 2024 The Editor(s) (if applicable) and The

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書目名稱Entropy Measures for Environmental Data影響因子(影響力)




書目名稱Entropy Measures for Environmental Data影響因子(影響力)學科排名




書目名稱Entropy Measures for Environmental Data網(wǎng)絡(luò)公開度




書目名稱Entropy Measures for Environmental Data網(wǎng)絡(luò)公開度學科排名




書目名稱Entropy Measures for Environmental Data被引頻次




書目名稱Entropy Measures for Environmental Data被引頻次學科排名




書目名稱Entropy Measures for Environmental Data年度引用




書目名稱Entropy Measures for Environmental Data年度引用學科排名




書目名稱Entropy Measures for Environmental Data讀者反饋




書目名稱Entropy Measures for Environmental Data讀者反饋學科排名

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Spatial Entropy Measures, the main approaches available in the literature for the consideration of the spatial dimension in entropy indices. In particular, Sect.?. contains Batty’s approach to spatial entropy for geographical data, and its extension for the inclusion of a neighbourhood system. Section?. outlines the other m

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Entropy Estimation,dependence structures. The idea is that the available observations are a (temporary) picture of an underlying and unknown process that governs the actual diversity of the system. Therefore, data are considered as a sample extracted from such process, and used for understanding what the latent hetero

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Linda Altieri,Daniela CocchiCovers both theoretical and practical aspects of entropy measures.Is the first book to deal with spatial entropy estimation for complex data.Provides examples and tutorials to make results understanda

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Advances in Geographical and Environmental Scienceshttp://image.papertrans.cn/f/image/320660.jpg

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https://doi.org/10.1057/9781403983589iples of entropy, initially introduced in Information Theory: we focus on the original entropy formula for categorical variables, and on its decomposition, that contains the potential for the extension to spatial entropy. The second Section focuses on environmental studies and provides some necessar

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Tshilidzi Marwala,Monica Lagaziod environmental data. Techniques are borrowed from the branch of spatial sampling, a collection of methods for extracting subsets of observations from a population, where the spatial location of occurrences is considered relevant for estimating the target characteristics, such as the mean or total o

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https://doi.org/10.1007/978-3-319-78229-4dependence structures. The idea is that the available observations are a (temporary) picture of an underlying and unknown process that governs the actual diversity of the system. Therefore, data are considered as a sample extracted from such process, and used for understanding what the latent hetero