Kirjahaku

This book discusses advanced topics such as R core programing, object oriented R programing, parallel computing with R, and spatial data types. The author leads readers to merge mature and effective methdologies in traditional programing to R programing. It shows how to interface R with C, Java, and other popular programing laguages and platforms.

Research and development of various parallel mechanism applications in engineering are now being performed more and more actively in every industrial field. Parallel robot based machine tools development is considered a key technology of robot applications in manufacturing industries. The material covered here describes the basic theory, approaches, and algorithms in the field of parallel robot based machine tools. In addition families of new alternative mechanical architectures which can be used for machine tools with parallel architecture are introduced. Given equal importance is the design of mechanism systems such as kinematic analysis, stiffness analysis, kinetostatic modeling, and optimization.

Research and development of various parallel mechanism applications in engineering are now being performed more and more actively in every industrial field. Parallel robot based machine tools development is considered a key technology of robot applications in manufacturing industries. The material covered here describes the basic theory, approaches, and algorithms in the field of parallel robot based machine tools. In addition families of new alternative mechanical architectures which can be used for machine tools with parallel architecture are introduced. Given equal importance is the design of mechanism systems such as kinematic analysis, stiffness analysis, kinetostatic modeling, and optimization.

Unlike other books about R, written from the perspective of statistics, R for Programmers: Mastering the Tools is written from the perspective of programmers, providing a channel for programmers with expertise in other programming languages to quickly understand R. The contents are divided into four sections: The first section consists of the basics of R, which explains the advantages of using R, the installation of different versions of R, and the 12 frequently used packages of R. This will help you understand the tool packages, time series packages, and performance monitoring packages of R quickly.The second section discusses the server of R, which examines the communication between R and other programming languages and the application of R as servers. This will help you integrate R with other programming languages and implement the server application of R. The third section discusses databases and big data, which covers the communication between R and various databases, as well as R’s integration with Hadoop. This will help you integrate R with the underlying level of other databases and implement the processing of big data by R, based on Hadoop.The fourth section comprises the appendices, which introduce the installation of Java, various databases, and Hadoop. Because this is a reference book, there is no special sequence for reading all the chapters. You can choose the chapters in which you have an interest. If you are new to R, and you wish to master R comprehensively, simply follow the chapters in sequence.

This book discusses advanced topics such as R core programing, object oriented R programing, parallel computing with R, and spatial data types. The author leads readers to merge mature and effective methdologies in traditional programing to R programing. It shows how to interface R with C, Java, and other popular programing laguages and platforms.

After the fundamental volume and the advanced technique volume, this volume focuses on R applications in the quantitative investment area. Quantitative investment has been hot for some years, and there are more and more startups working on it, combined with many other internet communities and business models. R is widely used in this area, and can be a very powerful tool. The author introduces R applications with cases from his own startup, covering topics like portfolio optimization and risk management.