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Titlebook: Evolutionary Statistical Procedures; An Evolutionary Comp Roberto Baragona,Francesco Battaglia,Irene Poli Book 2011 Springer-Verlag Berlin

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書目名稱Evolutionary Statistical Procedures
副標(biāo)題An Evolutionary Comp
編輯Roberto Baragona,Francesco Battaglia,Irene Poli
視頻videohttp://file.papertrans.cn/319/318023/318023.mp4
概述A reference for statistical researchers at an advanced graduate level or beyond.Deals with topics like time series data analysis, cluster analysis, design of experiments, outliers etc. that have pract
叢書名稱Statistics and Computing
圖書封面Titlebook: Evolutionary Statistical Procedures; An Evolutionary Comp Roberto Baragona,Francesco Battaglia,Irene Poli Book 2011 Springer-Verlag Berlin
描述.This proposed text appears to be a good introduction to evolutionary computation for use in applied statistics research. The authors draw from a vast base of knowledge about the current literature in both the design of evolutionary algorithms and statistical techniques. Modern statistical research is on the threshold of solving increasingly complex problems in high dimensions, and the generalization of its methodology to parameters whose estimators do not follow mathematically simple distributions is underway. Many of these challenges involve optimizing functions for which analytic solutions are infeasible. Evolutionary algorithms represent a powerful and easily understood means of approximating the optimum value in a variety of settings. The proposed text seeks to guide readers through the crucial issues of optimization problems in statistical settings and the implementation of tailored methods (including both stand-alone evolutionary algorithms and hybrid crosses of these procedures with standard statistical algorithms like Metropolis-Hastings) in a variety of applications. This book would serve as an excellent reference work for statistical researchers at an advanced graduate l
出版日期Book 2011
關(guān)鍵詞Data Analysis; Design of Experiments; Evolutionary Computation; Metaheuristics; Optimization Algorithms
版次1
doihttps://doi.org/10.1007/978-3-642-16218-3
isbn_softcover978-3-642-26654-6
isbn_ebook978-3-642-16218-3Series ISSN 1431-8784 Series E-ISSN 2197-1706
issn_series 1431-8784
copyrightSpringer-Verlag Berlin Heidelberg 2011
The information of publication is updating

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Evolving Regression Models,n their implementation and application in a wide number of fields are still the object of active research. Preliminary to the regression model estimation there is an identification step which has to be performed for selecting the variables of interest, detecting the relationships of interest among t
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Time Series Linear and Nonlinear Models,odel building has been extensively studied and well established both theory and practice allow the user to proceed along reliable guidelines. Ergodicity, stationarity and Gaussianity properties are generally assumed to ensure that the structure of a stochastic process may be estimated safely enough
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Design of Experiments,ient plan of experimentation is essential to achieve good results and avoid unnecessary waste of resources. An accurate statistical design of the experiments is important also to tackle the uncertainty in the experimental results derived from systematic and random errors that frequently obscure the
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Roberto Baragona,Francesco Battaglia,Irene PoliA reference for statistical researchers at an advanced graduate level or beyond.Deals with topics like time series data analysis, cluster analysis, design of experiments, outliers etc. that have pract
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