Introductory Statistics with R
R is an Open Source implementation of the S language. It works on multiple computing platforms and can be freely downloaded. ...
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Kernel Based Algorithms for Mining Huge Data Sets
"Kernel Based Algorithms for Mining Huge Data Sets" is the first book treating the fields of supervised, semi-supervised ...
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Knowledge Discovery in Inductive Databases
This book constitutes the thoroughly refereed joint postproceedings of the 5th International Workshop on Knowledge Discovery ...
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Knowledge Discovery in Inductive Databases (vol. # 3933)
The4thInternationalWorkshoponKnowledgeDiscoveryinInductiveDatabases (KDID 2005) was held in Porto, Portugal, on October 3, ...
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Linear Models and Generalizations: Least Squares and Alternatives
Thebookisbasedonseveralyearsofexperienceofbothauthorsinteaching linear models at various levels. It gives an up-to-date account ...
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Linear and Generalized Linear Mixed Models and Their Applications
This book covers two major classes of mixed effects models—linear mixed models and generalized linear mixed models—and ...
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Linear and Generalized Linear Mixed Models and Their Applications
This book covers two major classes of mixed effects models, linear mixed models and generalized linear mixed models, and ...
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Mathematics of Uncertainty
Mathematics of Uncertainty" provides the basic ideas and foundations of uncertainty, covering the fields of mathematics ...
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Modeling Longitudinal Data
This book teaches the art and statistical science of modern longitudinal data analysis. The author emphasizes specifying, ...
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Modeling Uncertainty
Modeling Uncertainty: An Examination of Stochastic Theory, Methods, and Applications, is a volume undertaken by the friends ...
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Modelling and Reasoning with Vague Concepts
This volume outlines a formal representation framework for modelling and reasoning with vague concepts in Artificial Intelligence. ...
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Modern Econometric Analysis
The importance of empirical economics and econometric methods has greatly in creased during the last 20 years due to the ...
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Modern Mathematical Statistics with Applications
This book tries to strike a balance between mathematical foundations and statistical practice. The book provides a clear ...
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Monte Carlo Methods in Fuzzy Optimization
This book is a concise and readable introduction to Monte Carlo methods to find good approximate solutions to fuzzy optimization ...
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This book brings together the latest genome base prediction models currently being used by statisticians, breeders and data ...
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Neural Networks and Deep Learning / Charu C. Aggarwal
Covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. ...
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New Developments in Classification and Data Analysis
This volume contains revised versions of selected papers presented during the biannual meeting of the Classification and ...
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New Introduction to Multiple Time Series Analysis
This reference work and graduate level textbook considers a wide range of models and methods for analyzing and forecasting ...
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Permutation Methods
This second edition places increased emphasis on the use of alternative permutation statistical tests based on metric Euclidean ...
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Principles of Mathematics in Operations Research
Principles of Mathematics in Operations Research is a comprehensive survey of the mathematical concepts and principles of ...
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