Optimal Resource Allocation: With Practical Statistical Applications and Theory
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- Optimal Resource Allocation: With Practical Statistical Applications and Theory by Igor A. Ushakov.
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Optimal Resource Allocation: With Practical Statistical Applications and Theory by Igor A. Ushakov
A Matrix Handbook for Statisticians 2. An Introduction to Linear Analysis 4. An elementary introduction to statistical learning theory 6. Applied Mixed Models in Medicine Convexity and optimization in R-n 1 7. Applications to Signal and Image Processing An Elementary Approach with Applications Finite mixture models Fourier series and numerical methods for partial differential equations Fundamental Probability — A Computational Approach General linear methods for ordinary differential equations Generalized least squares Introduction to linear models and statistical inference Introduction to Meta-Analysis Introduction to nonparametric regression The Theory and Application of Analysis of Variance Methodology of Longitudinal Surveys Modes of parametric statistical inference Theory and Algorithms, Third Edition Regression Analysis by Example, Fourth Edition Regression models for time series analysis Robust Methods in Biostatistics Scaling, fractals and wavelets Shape and shape theory Short-memory linear processes and econometric applications Small area estimation Density Estimation and Visualization Statistical methods for fuzzy data Statistical methods for trend detection and analysis in the environmental sciences Statistical modeling by wavelets Statistical Rules of Thumb, Second Edition Statistics for earth and environmental scientists