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Complex Data Modeling and Computationally Intensive Statistical Methods / by Pietro Mantovan, Piercesare Secchi
(Contributions to Statistics. ISSN:26288966)
版 | 1st ed. 2010. |
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出版者 | (Milano : Springer Milan : Imprint: Springer) |
出版年 | 2010 |
本文言語 | 英語 |
大きさ | X, 170 p : online resource |
著者標目 | *Mantovan, Pietro author Secchi, Piercesare author SpringerLink (Online service) |
件 名 | LCSH:Computer software LCSH:Mathematical statistics -- Data processing 全ての件名で検索 LCSH:Statistics LCSH:Data mining FREE:Mathematical Software FREE:Statistics and Computing FREE:Statistical Theory and Methods FREE:Data Mining and Knowledge Discovery |
一般注記 | Space-time texture analysis in thermal infrared imaging for classification of Raynaud’s Phenomenon -- Mixed-effects modelling of Kevlar fibre failure times through Bayesian non-parametrics -- Space filling and locally optimal designs for Gaussian Universal Kriging -- Exploitation, integration and statistical analysis of the Public Health Database and STEMI Archive in the Lombardia region -- Bootstrap algorithms for variance estimation in ?PS sampling -- Fast Bayesian functional data analysis of basal body temperature -- A parametric Markov chain to model age- and state-dependent wear processes -- Case studies in Bayesian computation using INLA -- A graphical models approach for comparing gene sets -- Predictive densities and prediction limits based on predictive likelihoods -- Computer-intensive conditional inference -- Monte Carlo simulation methods for reliability estimation and failure prognostics 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 HTTP:URL=https://doi.org/10.1007/978-88-470-1386-5 |
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電子ブック | 配架場所 | 資料種別 | 巻 次 | 請求記号 | 状 態 | 予約 | コメント | ISBN | 刷 年 | 利用注記 | 指定図書 | 登録番号 |
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電子ブック | オンライン | 電子ブック |
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Springer eBooks | 9788847013865 |
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EB00237860 |
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データ種別 | 電子ブック |
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分 類 | LCC:QA76.75-76.765 DC23:510,285 |
書誌ID | 4000117081 |
ISBN | 9788847013865 |
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※2017年9月4日以降