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. There are six chapters in this book, categorized into three parts: Financial Market and Financial Theory, Data Processing and High Performance Computing of R, and Financial Strategy Practice. Every chapter is a holistic knowledge system. Section One is Financial Market and Financial Theory (including Chapters 1 and 2), which starts with an understanding of finance to establish a basic idea of financial quantification. Chapter 1, Financial Market Overview, is the opening chapter of this book, which mainly introduces the ideas and methods of how to use R language to make quantitative investments. Chapter 2, Financial Theory, mainly introduces the classic theoretical models of finance and the R implementation methods. In Section Two, Data Processing and High Performance Computing of R (including Chapters 3 and 4), essential tools of R language for data processing and their usage are introduced in detail. Chapter 3, Data Processing of R, cored with the data processing technology of R, introduces the methods of processing different types of data with R language. In Chapter 4, High Performance Computing of R, three external technologies are introduced to help the performance of R language meet the production environment requirements. Section Three, Financial Strategy Practice (including Chapters 5 and 6), combines the R language technology and the financial market rules to solve the practical problems in financial quantification field. In Chapter 5, Bonds and Repurchase, readers can learn the market and the methods of low-risk investment. In Chapter 6, Quantitative Investment Strategy Cases, the investment research methods from theory to practice are introduced in whole. Since knowledge of different areas is comprehensively applied in this book, it is suggested that you read all the chapters in order. Some of the technical implementations mentioned in this book use the information from the other two books of the series, R for Programmers: Mastering the Tools and R2 for Programmers: Advanced Techniques, so it is recommended that you read those two as well.

迭代应用的最佳检查点策略 这项工作提供了一种最佳的检查点策略，可以保护迭代应用程序免受故障停止错误的影响。 我们考虑一个非常通用的框架，其中应用程序通过执行连续的迭代来重复相同的执行模式，并且每个迭代都由多个任务组成。 这些任务具有不同的执行长度和不同的检查点成本。 天真的策略和Young / Daly策略都不理想。 我们的主要贡献是证明最佳检查点策略是全局周期性的，并设计一种动态编程算法来计算最佳检查点模式。 这种模式很可能会检查许多不同的任务，并且涉及许多不同的迭代。 通过在综合和实际应用场景中进行的仿真，我们表明，最佳策略明显优于单纯策略和Young / Daly策略。 代码 gen_faults.m生成服从指数分布的故障main_GCR.m为GCR应用程序进行仿真main_gopi.m为神经科学应用程序进行仿真main_random.m对合成应用程序进行仿真Simulation_e

一本机器学习入门的好书，同时伴有大量R语言的例子，是用R语言敲开机器学习大门的不二书选！Springer出版的经典书籍，很接地气。

The theory and practice of time series analysis have developed rapidly since the appear- ance in 1970 of the seminal work of George E. P. Box and Gwilym M. Jenkins, Time Series Analysis: Forecasting and Control, now available in its third edition (1994) with co-author Gregory C. Reinsel. Many books on time series have appeared since then, but some of them give too little practical application, while others give too little theoretical background. This book attempts to present both application, and theory at a level acces- sible to a wide variety of students and practitioners. Our approach is to mix application and theory throughout the book as they are naturally needed.

qt5_applications-5.15.2.2.2-py3-none-win_amd64.whl

复杂网络的经典外文著作《Complex Networks Principles Methods and Applications》 Networks constitute the backbone of complex systems, from the human brain to computer communications, transport infrastructures to online social systems, metabolic reactions to financial markets. Characterising their structure improves our understanding of the physical, biological, economic and social phenomena that shape our world. Rigorous and thorough, this textbook presents a detailed overview of the new theory and methods of network science. Covering algorithms for graph exploration, node ranking and network generation, among the others, the book allows students to experiment with network models and real-world data sets, providing them with a deep understanding of the basics of network theory and its practical applications. Systems of growing complexity are examined in detail, challenging students to increase their level of skill. An engaging pre- sentation of the important principles of network science makes this the perfect reference for researchers and undergraduate and graduate students in physics, mathematics, engineering, biology, neuroscience and social sciences.

关于 drawio-desktop是一个基于的diagrams.net桌面应用程序。 draw.io是diagrams.net的旧名称，我们只是不想麻烦更改所有二进制文件的名称。 从下载构建的二进制文件。 安全 除了更新过程外，draw.io Desktop的设计目的是与Internet完全隔离。 这会在启动时检查github.com是否有较新版本，并从Github拥有的AWS S3存储桶中下载该版本。 所有JavaScript文件都是自包含的，内容安全策略禁止运行远程加载JavaScript。 不会从外部发送图表数据，也不会从外部发送有关应用程序使用情况的任何分析。 这意味着我们没有JavaScript实现的某些功能在Desktop构建中不起作用，即.vsd和Gliffy导入。 发展 draw.io是drawio-desktop的git子模块。 要获得两者，您需要递归克隆： git

Richard Szeliski著《计算机视觉：算法与应用》英文原版pdf全文。不建议英文不好的同学下载。

2019年新书（Kaizhu Huang • Amir Hussain • Qiu-Feng Wang Rui Zhang著）。内容包括神经网络基础理论，深度密度模、RNN模型，基于深度学习的汉字手写体和文本识别、自然语言处理、海洋数据分析方面应用。

Smoothing Splines Methods and Applications 包含文档和代码