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With new chapters on ODEs and Markov chains, the second edition of this highly recommended, best-selling book introduces scientific programming and stochastic modelling in a clear, practical, and thorough way. Readers learn programming by experimenting with the provided R code and data. Requiring no prior knowledge of programming or probability, the book shows them how to turn algorithms into code. It includes case studies that demonstrate the simulation techniques as well as numerous student projects and exercises.
This book demystifies the computational aspects of actuarial science, showing that even complex computations can usually be done without too much trouble. Using simple R code, the book helps readers understand the algorithms involved in actuarial computations. It also covers more advanced topics, such as parallel computing and C/C++ embedded codes. Datasets used in the text are available in an R package (CASdatasets).
This book demystifies the computational aspects of actuarial science, showing that even complex computations can usually be done without too much trouble. Using simple R code, the book helps readers understand the algorithms involved in actuarial computations. It also covers more advanced topics, such as parallel computing and C/C++ embedded codes. Datasets used in the text are available in an R package (CASdatasets).
Spatio-Temporal Statistics with R provides an accessible introduction to statistical analysis of spatio-temporal data, with hands-on applications of the statistical methods using R Labs found at the end of each chapter.
This book explains the details involved in solving real computational problems encountered in data analysis. It reveals the dynamic and iterative process by which data analysts approach a problem and reason about different ways of implementing solutions. The book¿s collection of projects, exercises, and sample solutions encompass practical topics pertaining to data processing and analysis. The book can be used for self-study or as supplementary reading in a statistical computing course, allowing students to gain valuable data science skills.
This book provides an introduction to the field of microeconometrics through the use of R. The focus is on applying current learning from the field to real world problems. It uses R to both teach the concepts of the field and show the reader how the techniques can be used.
This is the first book on how to create websites based on R Markdown. It makes it much easier to publish data analysis results and R computing/graphics output through websites. The book can be particularly useful to bloggers, and also generally useful to anyone who wants to create a professional personal website.
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