Mathematics and statistics for science, Sneyd, James Fewster, Rachel M. Mcgillivray, Duncan
Автор: Gauch, Jr Название: Scientific Method in Brief ISBN: 1107666724 ISBN-13(EAN): 9781107666726 Издательство: Cambridge Academ Рейтинг: Цена: 43290.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Specifically designed to enhance perspective and encourage productivity, this is a guide to the key principles of scientific method including deductive and inductive logic, probability, parsimony and hypothesis testing. The examples and case studies span the physical, biological and social sciences and also highlight science`s interrelationship with the humanities.
Автор: Gallager Название: Stochastic Processes ISBN: 1107039754 ISBN-13(EAN): 9781107039759 Издательство: Cambridge Academ Рейтинг: Цена: 74970.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This definitive textbook provides a solid introduction to stochastic processes, covering both theory and applications. It is written by one of the world`s leading information theorists, evolving over twenty years of graduate classroom teaching, and is accompanied by over 300 exercises, with online solutions for instructors.
Автор: Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong Название: Mathematics for Machine Learning ISBN: 110845514X ISBN-13(EAN): 9781108455145 Издательство: Cambridge Academ Рейтинг: Цена: 42230.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This self-contained textbook introduces all the relevant mathematical concepts needed to understand and use machine learning methods, with a minimum of prerequisites. Topics include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics.
Автор: Bookstein, Fred L., Название: Measuring and Reasoning ISBN: 1107024153 ISBN-13(EAN): 9781107024151 Издательство: Cambridge Academ Рейтинг: Цена: 51730.00 T Наличие на складе: Поставка под заказ. Описание: This exploration of empirical inference in science ranges over topics as diverse as the mass extinction of the dinosaurs, Peirce`s concept of abduction, multiple regression, and the analysis of patterns in astrophysics. At its heart is a formal description of the process by which scientific measurements support convincing explanations of the world around us.
Incorporating the latest R packages as well as new case studies and applications, Using R and RStudio for Data Management, Statistical Analysis, and Graphics, Second Edition covers the aspects of R most often used by statistical analysts. New users of R will find the book's simple approach easy to understand while more sophisticated users will appreciate the invaluable source of task-oriented information.
New to the Second Edition
The use of RStudio, which increases the productivity of R users and helps users avoid error-prone cut-and-paste workflows
New chapter of case studies illustrating examples of useful data management tasks, reading complex files, making and annotating maps, "scraping" data from the web, mining text files, and generating dynamic graphics
New chapter on special topics that describes key features, such as processing by group, and explores important areas of statistics, including Bayesian methods, propensity scores, and bootstrapping
New chapter on simulation that includes examples of data generated from complex models and distributions
A detailed discussion of the philosophy and use of the knitr and markdown packages for R
New packages that extend the functionality of R and facilitate sophisticated analyses
Reorganized and enhanced chapters on data input and output, data management, statistical and mathematical functions, programming, high-level graphics plots, and the customization of plots
Easily Find Your Desired Task
Conveniently organized by short, clear descriptive entries, this edition continues to show users how to easily perform an analytical task in R. Users can quickly find and implement the material they need through the extensive indexing, cross-referencing, and worked examples in the text. Datasets and code are available for download on a supplementary website.
Автор: Xie Y. Название: Dynamic Documents with R and knitr, Second Edition ISBN: 1498716962 ISBN-13(EAN): 9781498716963 Издательство: Taylor&Francis Рейтинг: Цена: 78590.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Quickly and Easily Write Dynamic Documents
Suitable for both beginners and advanced users, Dynamic Documents with R and knitr, Second Edition makes writing statistical reports easier by integrating computing directly with reporting. Reports range from homework, projects, exams, books, blogs, and web pages to virtually any documents related to statistical graphics, computing, and data analysis. The book covers basic applications for beginners while guiding power users in understanding the extensibility of the knitr package.
New to the Second Edition
A new chapter that introduces R Markdown v2
Changes that reflect improvements in the knitr package
New sections on generating tables, defining custom printing methods for objects in code chunks, the C/Fortran engines, the Stan engine, running engines in a persistent session, and starting a local server to serve dynamic documents
Boost Your Productivity in Statistical Report Writing and Make Your Scientific Computing with R Reproducible
Like its highly praised predecessor, this edition shows you how to improve your efficiency in writing reports. The book takes you from program output to publication-quality reports, helping you fine-tune every aspect of your report.
Автор: Van Mieghem, Piet. Название: Performance analysis of complex networks and systems / ISBN: 1107058600 ISBN-13(EAN): 9781107058606 Издательство: Cambridge Academ Рейтинг: Цена: 83430.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: A rigorous and self-contained guide to the mathematical, stochastic and graph theoretic methods needed to analyse the performance and robustness of complex networks and systems. Containing problems and solved solutions, the book is ideal for graduate students taking courses in performance analysis.
Автор: Ugarte Maria Dolores Название: Probability and Statistics with R ISBN: 1466504390 ISBN-13(EAN): 9781466504394 Издательство: Taylor&Francis Рейтинг: Цена: 50160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Cohesively Incorporates Statistical Theory with R Implementation
Since the publication of the popular first edition of this comprehensive textbook, the contributed R packages on CRAN have increased from around 1,000 to over 6,000. Designed for an intermediate undergraduate course, Probability and Statistics with R, Second Edition explores how some of these new packages make analysis easier and more intuitive as well as create more visually pleasing graphs.
New to the Second Edition
Improvements to existing examples, problems, concepts, data, and functions
New examples and exercises that use the most modern functions
Coverage probability of a confidence interval and model validation
Highlighted R code for calculations and graph creation
Gets Students Up to Date on Practical Statistical Topics
Keeping pace with today's statistical landscape, this textbook expands your students' knowledge of the practice of statistics. It effectively links statistical concepts with R procedures, empowering students to solve a vast array of real statistical problems with R.
Web Resources
A supplementary website offers solutions to odd exercises and templates for homework assignments while the data sets and R functions are available on CRAN.
Автор: Heeringa Название: Applied Survey Data Analysis, Second Edition ISBN: 1498761607 ISBN-13(EAN): 9781498761604 Издательство: Taylor&Francis Рейтинг: Цена: 91860.00 T Наличие на складе: Нет в наличии. Описание: This book provides an overview of state-of-the-art approaches to the analysis of complex sample survey data. Building on the wealth of material on practical approaches to descriptive analysis and regression modeling from the first edition, this second edition expands the topics covered and presents more examples the analysis of survey data.
Автор: Ghahramani Название: Fndmntls Of Probability 4E ISBN: 1498755097 ISBN-13(EAN): 9781498755092 Издательство: Taylor&Francis Рейтинг: Цена: 112290.00 T Наличие на складе: Нет в наличии. Описание: Covers topics used in a calculus-based junior-senior probability course. It can also be used as a text for a second course in probability. The historical roots and applications of many of the theorems and definitions are presented in detail, accompanied by suitable examples or counterexamples.
Автор: Bergomi Название: Stochastic Volatility Modeling ISBN: 1482244063 ISBN-13(EAN): 9781482244069 Издательство: Taylor&Francis Рейтинг: Цена: 89820.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Packed with insights, Lorenzo Bergomi's Stochastic Volatility Modeling explains how stochastic volatility is used to address issues arising in the modeling of derivatives, including:
Which trading issues do we tackle with stochastic volatility?
How do we design models and assess their relevance?
How do we tell which models are usable and when does calibration make sense?
This manual covers the practicalities of modeling local volatility, stochastic volatility, local-stochastic volatility, and multi-asset stochastic volatility. In the course of this exploration, the author, Risk's 2009 Quant of the Year and a leading contributor to volatility modeling, draws on his experience as head quant in Soci t G n rale's equity derivatives division. Clear and straightforward, the book takes readers through various modeling challenges, all originating in actual trading/hedging issues, with a focus on the practical consequences of modeling choices.
Автор: Efron Название: An Introduction to the Bootstrap ISBN: 0412042312 ISBN-13(EAN): 9780412042317 Издательство: Taylor&Francis Рейтинг: Цена: 153120.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: An exploration of the many different bootstrap techniques. It discusses useful statistical techniques through real data examples and covers nonparametric regression, density estimation, classification trees, and least median squares regression. There are numerous exercises.
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