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Titlebook: Complex Data Modeling and Computationally Intensive Statistical Methods; Pietro Mantovan,Piercesare Secchi Book 2010 Springer-Verlag Milan

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發(fā)表于 2025-3-21 18:24:16 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Complex Data Modeling and Computationally Intensive Statistical Methods
編輯Pietro Mantovan,Piercesare Secchi
視頻videohttp://file.papertrans.cn/232/231416/231416.mp4
概述The book offers a wide variety of statistical methods and is addressed to statisticians working at the forefront of statistical analysis
叢書名稱Contributions to Statistics
圖書封面Titlebook: Complex Data Modeling and Computationally Intensive Statistical Methods;  Pietro Mantovan,Piercesare Secchi Book 2010 Springer-Verlag Milan
描述.The last years have seen the advent and development of many devices able to record and store an always increasing amount of complex and high dimensional data; 3D images generated by medical scanners or satellite remote sensing, DNA microarrays, real time financial data, system control datasets, .... ..The analysis of this data poses new challenging problems and requires the development of novel statistical models and computational methods, fueling many fascinating and fast growing research areas of modern statistics. The book offers a wide variety of statistical methods and is addressed to statisticians working at the forefront of statistical analysis..
出版日期Book 2010
關(guān)鍵詞Likelihood; STATISTICA; Time series; Variance; bayesian statistics; biodata mining; classification; classif
版次1
doihttps://doi.org/10.1007/978-88-470-1386-5
isbn_softcover978-88-470-5806-4
isbn_ebook978-88-470-1386-5Series ISSN 1431-1968 Series E-ISSN 2628-8966
issn_series 1431-1968
copyrightSpringer-Verlag Milan 2010
The information of publication is updating

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Fast Bayesian functional data analysis of basal body temperature,present an application of the Relevant Vector Machine method that generates sparse functional linear and linear mixed models that can be used to rapidly estimate individual-specific and population average functions.
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A parametric Markov chain to model age- and state-dependent wear processes,sition probabilities between process states depend on both the current age and the current wear level of the system. An application based on a real data set referring to the wear process of the cylinder liners of heavy-duty diesel engines for marine propulsion is analysed and discussed.
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Case studies in Bayesian computation using INLA,LA, is a prototype of such black-box for inference on latent Gaussian models which is both flexible and user-friendly. It is meant to, hopefully,make latent Gaussian models applicable, useful and appealing for a larger class of users.
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發(fā)表于 2025-3-22 09:25:50 | 只看該作者
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發(fā)表于 2025-3-22 16:05:12 | 只看該作者
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