R is an Open Source implementation of the S language. It works on multiple computing platforms and can be freely downloaded. ...
Continue reading"Kernel Based Algorithms for Mining Huge Data Sets" is the first book treating the fields of supervised, semi-supervised ...
Continue readingThis book constitutes the thoroughly refereed joint postproceedings of the 5th International Workshop on Knowledge Discovery ...
Continue readingThe4thInternationalWorkshoponKnowledgeDiscoveryinInductiveDatabases (KDID 2005) was held in Porto, Portugal, on October 3, ...
Continue readingThebookisbasedonseveralyearsofexperienceofbothauthorsinteaching linear models at various levels. It gives an up-to-date account ...
Continue readingThis book covers two major classes of mixed effects models—linear mixed models and generalized linear mixed models—and ...
Continue readingThis book covers two major classes of mixed effects models, linear mixed models and generalized linear mixed models, and ...
Continue readingMathematics of Uncertainty" provides the basic ideas and foundations of uncertainty, covering the fields of mathematics ...
Continue readingThis book teaches the art and statistical science of modern longitudinal data analysis. The author emphasizes specifying, ...
Continue readingModeling Uncertainty: An Examination of Stochastic Theory, Methods, and Applications, is a volume undertaken by the friends ...
Continue readingThis volume outlines a formal representation framework for modelling and reasoning with vague concepts in Artificial Intelligence. ...
Continue readingThe importance of empirical economics and econometric methods has greatly in creased during the last 20 years due to the ...
Continue readingThis book tries to strike a balance between mathematical foundations and statistical practice. The book provides a clear ...
Continue readingThis book is a concise and readable introduction to Monte Carlo methods to find good approximate solutions to fuzzy optimization ...
Continue readingThis book brings together the latest genome base prediction models currently being used by statisticians, breeders and data ...
Continue readingCovers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. ...
Continue readingThis volume contains revised versions of selected papers presented during the biannual meeting of the Classification and ...
Continue readingThis reference work and graduate level textbook considers a wide range of models and methods for analyzing and forecasting ...
Continue readingThis second edition places increased emphasis on the use of alternative permutation statistical tests based on metric Euclidean ...
Continue readingPrinciples of Mathematics in Operations Research is a comprehensive survey of the mathematical concepts and principles of ...
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