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Author: Brian Gough Publisher: Network Theory. ISBN: 9780954612078 Category : Computers Languages : en Pages : 573
Book Description
The GNU Scientific Library (GSL) is a free numerical library for C and C++ programmers. It provides over 1,000 routines for solving mathematical problems in science and engineering. Written by the developers of GSL this reference manual is the definitive guide to the library. All the money raised from the sale of this book supports the development of the GNU Scientific Library. This is the third edition of the manual, and corresponds to version 1.12 of the library (updated January 2009).
Author: Brian Gough Publisher: Network Theory. ISBN: 9780954612078 Category : Computers Languages : en Pages : 573
Book Description
The GNU Scientific Library (GSL) is a free numerical library for C and C++ programmers. It provides over 1,000 routines for solving mathematical problems in science and engineering. Written by the developers of GSL this reference manual is the definitive guide to the library. All the money raised from the sale of this book supports the development of the GNU Scientific Library. This is the third edition of the manual, and corresponds to version 1.12 of the library (updated January 2009).
Author: Ben Klemens Publisher: Princeton University Press ISBN: 1400828740 Category : Mathematics Languages : en Pages : 471
Book Description
Modeling with Data fully explains how to execute computationally intensive analyses on very large data sets, showing readers how to determine the best methods for solving a variety of different problems, how to create and debug statistical models, and how to run an analysis and evaluate the results. Ben Klemens introduces a set of open and unlimited tools, and uses them to demonstrate data management, analysis, and simulation techniques essential for dealing with large data sets and computationally intensive procedures. He then demonstrates how to easily apply these tools to the many threads of statistical technique, including classical, Bayesian, maximum likelihood, and Monte Carlo methods. Klemens's accessible survey describes these models in a unified and nontraditional manner, providing alternative ways of looking at statistical concepts that often befuddle students. The book includes nearly one hundred sample programs of all kinds. Links to these programs will be available on this page at a later date. Modeling with Data will interest anyone looking for a comprehensive guide to these powerful statistical tools, including researchers and graduate students in the social sciences, biology, engineering, economics, and applied mathematics.
Author: Jason Lachniet Publisher: Lulu.com ISBN: 0359329640 Category : Education Languages : en Pages : 156
Book Description
A brief introduction to scientific computing with GNU Octave. Designed as a textbook supplement for freshman and sophomore level linear algebra and calculus students.
Author: Dirk Eddelbuettel Publisher: Springer Science & Business Media ISBN: 146146868X Category : Computers Languages : en Pages : 236
Book Description
Rcpp is the glue that binds the power and versatility of R with the speed and efficiency of C++. With Rcpp, the transfer of data between R and C++ is nearly seamless, and high-performance statistical computing is finally accessible to most R users. Rcpp should be part of every statistician's toolbox. -- Michael Braun, MIT Sloan School of Management "Seamless R and C++ integration with Rcpp" is simply a wonderful book. For anyone who uses C/C++ and R, it is an indispensable resource. The writing is outstanding. A huge bonus is the section on applications. This section covers the matrix packages Armadillo and Eigen and the GNU Scientific Library as well as RInside which enables you to use R inside C++. These applications are what most of us need to know to really do scientific programming with R and C++. I love this book. -- Robert McCulloch, University of Chicago Booth School of Business Rcpp is now considered an essential package for anybody doing serious computational research using R. Dirk's book is an excellent companion and takes the reader from a gentle introduction to more advanced applications via numerous examples and efficiency enhancing gems. The book is packed with all you might have ever wanted to know about Rcpp, its cousins (RcppArmadillo, RcppEigen .etc.), modules, package development and sugar. Overall, this book is a must-have on your shelf. -- Sanjog Misra, UCLA Anderson School of Management The Rcpp package represents a major leap forward for scientific computations with R. With very few lines of C++ code, one has R's data structures readily at hand for further computations in C++. Hence, high-level numerical programming can be made in C++ almost as easily as in R, but often with a substantial speed gain. Dirk is a crucial person in these developments, and his book takes the reader from the first fragile steps on to using the full Rcpp machinery. A very recommended book! -- Søren Højsgaard, Department of Mathematical Sciences, Aalborg University, Denmark "Seamless R and C ++ Integration with Rcpp" provides the first comprehensive introduction to Rcpp. Rcpp has become the most widely-used language extension for R, and is deployed by over one-hundred different CRAN and BioConductor packages. Rcpp permits users to pass scalars, vectors, matrices, list or entire R objects back and forth between R and C++ with ease. This brings the depth of the R analysis framework together with the power, speed, and efficiency of C++. Dirk Eddelbuettel has been a contributor to CRAN for over a decade and maintains around twenty packages. He is the Debian/Ubuntu maintainer for R and other quantitative software, edits the CRAN Task Views for Finance and High-Performance Computing, is a co-founder of the annual R/Finance conference, and an editor of the Journal of Statistical Software. He holds a Ph.D. in Mathematical Economics from EHESS (Paris), and works in Chicago as a Senior Quantitative Analyst.
Author: Jose M. Garrido Publisher: CRC Press ISBN: 1482216795 Category : Computers Languages : en Pages : 458
Book Description
Introduction to Computational Modeling Using C and Open-Source Tools presents the fundamental principles of computational models from a computer science perspective. It explains how to implement these models using the C programming language. The software tools used in the book include the Gnu Scientific Library (GSL), which is a free software libra
Author: Hans Petter Langtangen Publisher: Springer Science & Business Media ISBN: 3662054507 Category : Computers Languages : en Pages : 743
Book Description
Scripting with Python makes you productive and increases the reliability of your scientific work. Here, the author teaches you how to develop tailored, flexible, and efficient working environments built from small programs (scripts) written in Python. The focus is on examples and applications of relevance to computational science: gluing existing applications and tools, e.g. for automating simulation, data analysis, and visualization; steering simulations and computational experiments; equipping programs with graphical user interfaces; making computational Web services; creating interactive interfaces with a Maple/Matlab-like syntax to numerical applications in C/C++ or Fortran; and building flexible object-oriented programming interfaces to existing C/C++ or Fortran libraries.
Author: Joe Pitt-Francis Publisher: Springer Science & Business Media ISBN: 1447127366 Category : Computers Languages : en Pages : 257
Book Description
This easy-to-read textbook/reference presents an essential guide to object-oriented C++ programming for scientific computing. With a practical focus on learning by example, the theory is supported by numerous exercises. Features: provides a specific focus on the application of C++ to scientific computing, including parallel computing using MPI; stresses the importance of a clear programming style to minimize the introduction of errors into code; presents a practical introduction to procedural programming in C++, covering variables, flow of control, input and output, pointers, functions, and reference variables; exhibits the efficacy of classes, highlighting the main features of object-orientation; examines more advanced C++ features, such as templates and exceptions; supplies useful tips and examples throughout the text, together with chapter-ending exercises, and code available to download from Springer.
Author: Jim Davies Publisher: Simon and Schuster ISBN: 1643136518 Category : Science Languages : en Pages : 342
Book Description
A crisp and sparkling blend of cognitive science and human behavior that offers meaningful and attainable pathways towards becoming our best selves. Why do we feel like in order to be productive, happy, or good, we must sacrifice everything else? Is it possible to feel all three at once? Without even knowing it, we’re doing things everyday to sabotage ourselves and our societies, habits that prevent us from optimizing long term happiness. Where most books imagine solutions that, when enacted, fail to fundamentally improve our lives, Jim Davies grounds his research in cognitive science to show you not only what works, but how much it works. Being the Person Your Dog Thinks You Are shows us how we can use science to become our best selves, using resources we already have within our own brains. Davies's book challenges and inspires us to approach the big picture while also staying mindful of the everyday details in real life. Davies proves why multitasking is bad for you, when a little unmindfulness can be good for you, how to best justify which charities to donate to, and how to hack your brain. The most surprising truth Davies offers us spreads across these pages like wildfire: you too can lead an optimally good life, not through uprooting your life from the ground up, but from adapting your mentality to your given present. A better life doesn’t need to look like a massive change—like our beloved dogs who already view us as our best selves, it’s already much closer than you think.
Author: Philipp K. Janert Publisher: "O'Reilly Media, Inc." ISBN: 1449396658 Category : Computers Languages : en Pages : 534
Book Description
Collecting data is relatively easy, but turning raw information into something useful requires that you know how to extract precisely what you need. With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through business plans, metrics dashboards, and other applications. Along the way, you'll experiment with concepts through hands-on workshops at the end of each chapter. Above all, you'll learn how to think about the results you want to achieve -- rather than rely on tools to think for you. Use graphics to describe data with one, two, or dozens of variables Develop conceptual models using back-of-the-envelope calculations, as well asscaling and probability arguments Mine data with computationally intensive methods such as simulation and clustering Make your conclusions understandable through reports, dashboards, and other metrics programs Understand financial calculations, including the time-value of money Use dimensionality reduction techniques or predictive analytics to conquer challenging data analysis situations Become familiar with different open source programming environments for data analysis "Finally, a concise reference for understanding how to conquer piles of data."--Austin King, Senior Web Developer, Mozilla "An indispensable text for aspiring data scientists."--Michael E. Driscoll, CEO/Founder, Dataspora
Author: Brian Gough
Author: Brian Gough
Author: Ben Klemens
Author: Jason Lachniet
Author: Dirk Eddelbuettel
Author: Jose M. Garrido
Author: Hans Petter Langtangen
Author: Joe Pitt-Francis
Author: Jim Davies
Author: Philipp K. Janert
Author: Richard Stallman