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 Robust Statistics: Theory and Methods (Probability and Statistics)Classical statistical techniques fail to cope well with deviations from a standard distribution. Robust statistical methods take into account these deviations while estimating the parameters of parametric models, thus increasing the accuracy of the inference. Research into robust methods is flourishing, with new methods being developed and... |  |  |  |  |
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 MATLAB Linear Algebra
MATLAB is a high-level language and environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or... |  |  Nonparametric System IdentificationPresenting a thorough overview of the theoretical foundations of non-parametric system identification for nonlinear block-oriented systems, this books shows that non-parametric regression can be successfully applied to system identification, and it highlights the achievements in doing so. With emphasis on Hammerstein, Wiener systems, and their... |  |  Six Sigma and Beyond: Statistics and Probability, Volume IIIThis text explains the tools of statistics and how to apply them effectively to improve processes and profitability in an organization, and also delineates the importance of collecting, analyzing, and interpreting data.
Researchers and professionals in all walks of life need to use the many tools offered by the statistical world, but... |
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