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Statistical Tools for Nonlinear Regression: A Practical Guide With S-PLUS and R Examples (Springer Series in Statistics)

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Statistical Tools for Nonlinear Regression presents methods for analyzing data. It has been expanded to include binomial, multinomial and Poisson non-linear models. The examples are analyzed with the free software nls2 updated to deal with the new models included in the second edition. The nls2 package is implemented in S-PLUS and R. Several additional tools are included in the package for calculating confidence regions for functions of parameters or calibration intervals, using classical methodology or bootstrap.

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Practical Optimization Methods: With Mathematica® Applications
Practical Optimization Methods: With Mathematica® Applications
This introductory textbook adopts a practical and intuitive approach, rather than emphasizing mathematical rigor. Computationally oriented books in this area generally present algorithms alone, and expect readers to perform computations by hand, and are often written in traditional computer languages, such as Basic, Fortran or Pascal. This book,...
Clustering for Data Mining: A Data Recovery Approach (Chapman & Hall/CRC Computer Science & Data Analysis)
Clustering for Data Mining: A Data Recovery Approach (Chapman & Hall/CRC Computer Science & Data Analysis)
Often considered more as an art than a science, the field of clustering has been dominated by learning through examples and by techniques chosen almost through trial-and-error. Even the most popular clustering methods--K-Means for partitioning the data set and Ward's method for hierarchical clustering--have lacked the theoretical...
Simulation and Inference for Stochastic Differential Equations: With R Examples (Springer Series in Statistics)
Simulation and Inference for Stochastic Differential Equations: With R Examples (Springer Series in Statistics)

This book covers a highly relevant and timely topic that is of wide interest, especially in finance, engineering and computational biology. The introductory material on simulation and stochastic differential equation is very accessible and will prove popular with many readers. While there are several recent texts available that cover...


Finite Element Modeling for Materials Engineers Using MATLAB®
Finite Element Modeling for Materials Engineers Using MATLAB®

The finite element method is often used for numerical computation in the applied sciences. It makes a major contribution to the range of numerical methods used in the simulation of systems and irregular domains, and its importance today has made it an important subject of study for all engineering students.
 
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Modular Algorithms in Symbolic Summation and Symbolic Integration (Lecture Notes in Computer Science)
Modular Algorithms in Symbolic Summation and Symbolic Integration (Lecture Notes in Computer Science)
This work brings together two streams in computer algebra: symbolic integration and summation on the one hand, and fast algorithmics on the other hand. In many algorithmically oriented areas of computer science, theanalysisof- gorithms–placedintothe limelightbyDonKnuth’stalkat the 1970ICM –provides a crystal-clear criterion for...
Practical Algorithms for 3D Computer Graphics, Second Edition
Practical Algorithms for 3D Computer Graphics, Second Edition

Practical Algorithms for 3D Computer Graphics, Second Edition covers the fundamental algorithms that are the core of all 3D computer graphics software packages. Using Core OpenGL and OpenGL ES, the book enables you to create a complete suite of programs for 3D computer animation, modeling, and image synthesis.

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