Mathematical Modeling: Models, Analysis And Applications

Mathematical Modeling: Models, Analysis and Applications, 2nd Edition  eBooks & eLearning

Posted by yoyoloit at July 25, 2023
Mathematical Modeling: Models, Analysis and Applications, 2nd Edition

Mathematical Modeling; Models, Analysis and Applications; Second Edition
by Sandip Banerjee

English | 2022 | ISBN: 1138495948 | 434 pages | True PDF | 33.23 MB

Mathematical Modeling: Models, Analysis and Applications [Repost]  eBooks & eLearning

Posted by ChrisRedfield at Jan. 24, 2017
Mathematical Modeling: Models, Analysis and Applications [Repost]

Sandip Banerjee - Mathematical Modeling: Models, Analysis and Applications
Published: 2014-02-07 | ISBN: 1439854513 | PDF | 276 pages | 2.64 MB

Linear Regression : Models, Analysis, and Applications  eBooks & eLearning

Posted by readerXXI at Aug. 21, 2018
Linear Regression : Models, Analysis, and Applications

Linear Regression : Models, Analysis, and Applications
by Vera L. Beck
English | 2017 | ISBN: 153611992X | 193 Pages | PDF | 3.8 MB

Mixed Models: Theory and Applications with R, Second Edition  eBooks & eLearning

Posted by AvaxGenius at Oct. 9, 2022
Mixed Models: Theory and Applications with R, Second Edition

Mixed Models: Theory and Applications with R, Second Edition by Eugene Demidenko
English | PDF | 2013 | 756 Pages | ISBN : 1118091574 | 38.3 MB

Mixed modeling is a crucial area of statistics, enabling the analysis of clustered and longitudinal data. Mixed Models: Theory and Applications with R, Second Edition fills a gap in existing literature between mathematical and applied statistical books by presenting a powerful examination of mixed model theory and application with special attention given to the implementation in R.

Mixed Models: Theory and Applications  eBooks & eLearning

Posted by AvaxGenius at Oct. 17, 2022
Mixed Models: Theory and Applications

Mixed Models: Theory and Applications by Eugene Demidenko
English | PDF | 2004 | 728 Pages | ISBN : 0471601616 | 41 MB

A rigorous, self-contained examination of mixed model theory and application
Mixed modeling is one of the most promising and exciting areas of statistical analysis, enabling the analysis of nontraditional, clustered data that may come in the form of shapes or images. This book provides in-depth mathematical coverage of mixed models’ statistical properties and numerical algorithms, as well as applications such as the analysis of tumor regrowth, shape, and image.
Density Functional Theory: Modeling, Mathematical Analysis, Computational Methods, and Applications

Density Functional Theory: Modeling, Mathematical Analysis, Computational Methods, and Applications by Eric Cancès, Gero Friesecke
English | PDF EPUB (True) | 2023 | 595 Pages | ISBN : 303122339X | 50 MB

Density functional theory (DFT) provides the most widely used models for simulating molecules and materials based on the fundamental laws of quantum mechanics. It plays a central role in a huge spectrum of applications in chemistry, physics, and materials science.Quantum mechanics describes a system of N interacting particles in the physical 3-dimensional space by a partial differential equation in 3N spatial variables. The standard numerical methods thus incur an exponential increase of computational effort with N, a phenomenon known as the curse of dimensionality; in practice these methods already fail beyond N=2.

Advanced Mathematical Modeling with Technology  eBooks & eLearning

Posted by yoyoloit at May 26, 2021
Advanced Mathematical Modeling with Technology

Advanced Mathematical Modeling with Technology (Advances in Applied Mathematics)
by William P. Fox

English | 2021 | ISBN: 9780367494421, 0367494426 | 573 pages | True PDF | 36.96 MB

Mathematical modeling is both a skill and an art and must be practiced in order to maintain and enhance the ability to use those skills. Though the topics covered in this book are the typical topics of most mathematical modeling courses, this book is best used for individuals or groups who have already taken an introductory mathematical modeling course. Advanced Mathematical Modeling with Technology will be of interest to instructors and students offering courses focused on discrete modeling or modeling for decision making.

Mathematical Modeling the Life Sciences : Numerical Recipes in Python and MATLAB®  eBooks & eLearning

Posted by readerXXI at Dec. 22, 2022
Mathematical Modeling the Life Sciences : Numerical Recipes in Python and MATLAB®

Mathematical Modeling the Life Sciences : Numerical Recipes in Python and MATLAB®
by N. G. Cogan
English | 2023 | ISBN: 0367554933 | 232 Pages | True ePUB | 5.24 MB

Cellular Automata: Analysis and Applications  eBooks & eLearning

Posted by AvaxGenius at May 27, 2017
Cellular Automata: Analysis and Applications

Cellular Automata: Analysis and Applications By Karl-Peter Hadeler, Johannes Müller
English | PDF | 2017 | 467 Pages | ISBN : 3319530429 | 7.3 MB

This book focuses on a coherent representation of the main approaches to analyze the dynamics of cellular automata. Cellular automata are an inevitable tool in mathematical modeling. In contrast to classical modeling approaches as partial differential equations, cellular automata are straightforward to simulate but hard to analyze.

Nonsmooth/Nonconvex Mechanics: Modeling, Analysis and Numerical Methods  eBooks & eLearning

Posted by AvaxGenius at Feb. 21, 2022
Nonsmooth/Nonconvex Mechanics: Modeling, Analysis and Numerical Methods

Nonsmooth/Nonconvex Mechanics: Modeling, Analysis and Numerical Methods by David Y. Gao
English | PDF | 2001 | 505 Pages | ISBN : 0792367863 | 41.3 MB

Nonsmooth and nonconvex models arise in several important applications of mechanics and engineering. The interest in this field is growing from both mathematicians and engineers. The study of numerous industrial applications, including contact phenomena in statics and dynamics or delamination effects in composites, require the consideration of nonsmoothness and nonconvexity. The mathematical topics discussed in this book include variational and hemivariational inequalities, duality, complementarity, variational principles, sensitivity analysis, eigenvalue and resonance problems, and minimax problems.