Book picks similar to
Applied Time Series Econometrics by Helmut Lütkepohl


econometrics
economics
mat
time-series-and-forecasting

On Being a Data Skeptic


Cathy O'Neil - 2013
    Data is nuanced, and "a really excellent skeptic puts the term 'science' into 'data science.'" The big data revolution shouldn't be dismissed as hype, but current data science tools and models shouldn't be hailed as the end-all-be-all, either."

Biochemical Engineering Fundamentals


James E. Bailey - 1977
    The biological background provided enables students to comprehend the major problems in biochemical engineering and formulate effective solutions.

Bitcoin and Cryptocurrency Technologies: A Comprehensive Introduction


Arvind Narayanan - 2016
    Whether you are a student, software developer, tech entrepreneur, or researcher in computer science, this authoritative and self-contained book tells you everything you need to know about the new global money for the Internet age.How do Bitcoin and its block chain actually work? How secure are your bitcoins? How anonymous are their users? Can cryptocurrencies be regulated? These are some of the many questions this book answers. It begins by tracing the history and development of Bitcoin and cryptocurrencies, and then gives the conceptual and practical foundations you need to engineer secure software that interacts with the Bitcoin network as well as to integrate ideas from Bitcoin into your own projects. Topics include decentralization, mining, the politics of Bitcoin, altcoins and the cryptocurrency ecosystem, the future of Bitcoin, and more.An essential introduction to the new technologies of digital currencyCovers the history and mechanics of Bitcoin and the block chain, security, decentralization, anonymity, politics and regulation, altcoins, and much moreFeatures an accompanying website that includes instructional videos for each chapter, homework problems, programming assignments, and lecture slidesAlso suitable for use with the authors' Coursera online courseElectronic solutions manual (available only to professors)

Introductory Statistics with R


Peter Dalgaard - 2002
    It can be freely downloaded and it works on multiple computer platforms. This book provides an elementary introduction to R. In each chapter, brief introductory sections are followed by code examples and comments from the computational and statistical viewpoint. A supplementary R package containing the datasets can be downloaded from the web.

Introductory Statistics


Prem S. Mann - 2006
    The realistic content of its examples and exercises, the clarity and brevity of its presentation, and the soundness of its pedagogical approach have received the highest remarks from both students and instructors. Now this bestseller is available in a new 6th edition.

Frequently Asked Questions in Quantitative Finance


Paul Wilmott - 2007
    It is fascinating because of the speed at which the subject develops, the new products and the new models which we have to understand. And it is rewarding because anyone can make a fundamental breakthrough."Having worked in this field for many years, I have come to appreciate the importance of getting the right balance between mathematics and intuition. Too little maths and you won't be able to make much progress, too much maths and you'll be held back by technicalities. I imagine, but expect I will never know for certain, that getting the right level of maths is like having the right equipment to climb Mount Everest; too little and you won't make the first base camp, too much and you'll collapse in a heap before the top."Whenever I write about or teach this subject I also aim to get the right mix of theory and practice. Finance is not a hard science like physics, so you have to accept the limitations of the models. But nor is it a very soft science, so without those models you would be at a disadvantage compared with those better equipped. I believe this adds to the fascination of the subject."This FAQs book looks at some of the most important aspects of financial engineering, and considers them from both theoretical and practical points of view. I hope that you will see that finance is just as much fun in practice as in theory, and if you are reading this book to help you with your job interviews, good luck! Let me know how you get on!"

How to Count to Infinity


Marcus du Sautoy - 2020
    But this book will help you to do something that humans have only recently understood how to do: to count to regions that no animal has ever reached. By the end of this book you'll be able to count to infinity... and beyond. On our way to infinity we'll discover how the ancient Babylonians used their bodies to count to 60 (which gave us 60 minutes in the hour), how the number zero was only discovered in the 7th century by Indian mathematicians contemplating the void, why in China going into the red meant your numbers had gone negative and why numbers might be our best language for communicating with alien life.But for millennia, contemplating infinity has sent even the greatest minds into a spin. Then at the end of the nineteenth century mathematicians discovered a way to think about infinity that revealed that it is a number that we can count. Not only that. They found that there are an infinite number of infinities, some bigger than others. Just using the finite neurons in your brain and the finite pages in this book, you'll have your mind blown discovering the secret of how to count to infinity.Do something amazing and learn a new skill thanks to the Little Ways to Live a Big Life books!

Probability Theory: The Logic of Science


E.T. Jaynes - 1999
    It discusses new results, along with applications of probability theory to a variety of problems. The book contains many exercises and is suitable for use as a textbook on graduate-level courses involving data analysis. Aimed at readers already familiar with applied mathematics at an advanced undergraduate level or higher, it is of interest to scientists concerned with inference from incomplete information.

Bayesian Data Analysis


Andrew Gelman - 1995
    Its world-class authors provide guidance on all aspects of Bayesian data analysis and include examples of real statistical analyses, based on their own research, that demonstrate how to solve complicated problems. Changes in the new edition include:Stronger focus on MCMC Revision of the computational advice in Part III New chapters on nonlinear models and decision analysis Several additional applied examples from the authors' recent research Additional chapters on current models for Bayesian data analysis such as nonlinear models, generalized linear mixed models, and more Reorganization of chapters 6 and 7 on model checking and data collectionBayesian computation is currently at a stage where there are many reasonable ways to compute any given posterior distribution. However, the best approach is not always clear ahead of time. Reflecting this, the new edition offers a more pluralistic presentation, giving advice on performing computations from many perspectives while making clear the importance of being aware that there are different ways to implement any given iterative simulation computation. The new approach, additional examples, and updated information make Bayesian Data Analysis an excellent introductory text and a reference that working scientists will use throughout their professional life.

A Student's Guide to Maxwell's Equations


Daniel Fleisch - 2007
    In this guide for students, each equation is the subject of an entire chapter, with detailed, plain-language explanations of the physical meaning of each symbol in the equation, for both the integral and differential forms. The final chapter shows how Maxwell's equations may be combined to produce the wave equation, the basis for the electromagnetic theory of light. This book is a wonderful resource for undergraduate and graduate courses in electromagnetism and electromagnetics. A website hosted by the author at www.cambridge.org/9780521701471 contains interactive solutions to every problem in the text as well as audio podcasts to walk students through each chapter.

Social and Economic Networks


Matthew O. Jackson - 2008
    The many aspects of our lives that are governed by social networks make it critical to understand how they impact behavior, which network structures are likely to emerge in a society, and why we organize ourselves as we do. In Social and Economic Networks, Matthew Jackson offers a comprehensive introduction to social and economic networks, drawing on the latest findings in economics, sociology, computer science, physics, and mathematics. He provides empirical background on networks and the regularities that they exhibit, and discusses random graph-based models and strategic models of network formation. He helps readers to understand behavior in networked societies, with a detailed analysis of learning and diffusion in networks, decision making by individuals who are influenced by their social neighbors, game theory and markets on networks, and a host of related subjects. Jackson also describes the varied statistical and modeling techniques used to analyze social networks. Each chapter includes exercises to aid students in their analysis of how networks function.This book is an indispensable resource for students and researchers in economics, mathematics, physics, sociology, and business.

Elementary Number Theory


David M. Burton - 1976
    It reveals the attraction that has drawn leading mathematicians and amateurs alike to number theory over the course of history.

Introduction to Error Analysis: The Study of Uncertainties in Physical Measurements


John R. Taylor - 1982
    It is designed as a reference for students in the physical sciences and engineering.

CNC Programming Handbook


Peter Smid - 2000
    Used in hundreds of educational institutions around the world as the primary text for CNC courses, and used daily by many in-field CNC programmers and machine operators, this book literally defines CNC programming. Written with careful attention to detail, there are no compromises. Many of the changes in this new Third Edition are the direct result of comments and suggestions received from many CNC professionals in the field. This extraordinarily comprehensive work continues to be packed with over one thousand illustrations, tables, formulas, tips, shortcuts, and practical examples.The enclosed CD-ROM now contains a fully functional 15-day shareware version of CNC tool path editor/simulator, NCPlot™. This powerful, easy-to-learn software includes an amazing array of features, many not found in competitive products. NCPlot offers an unmatched combination of simplicity of use and richness of features. Support for many advanced control options is standard, including a macro interpreter that simulates Fanuc and similar macro programs.The CD-ROM also offers many training exercises based on individual chapters, along with solutions and detailed explanations. Special programming and machining examples are provided as well, in form of complete machine files, useful as actual programming resources. Virtually all files use Adobe PDF format and are set to high resolution printing.FEATURES Fully functional shareware version of CNC toolpath simulator/editor, NCPlot(TM), included on the CD-ROM. This powerful software includes an amazing array of features, including those not found in competitive products. Support for many advanced features is standard, and the included macro interpreter can simulate Fanuc and compatible macro toolpath programs Detailed section on CNC lathes with live tooling, including examples Image files of many actual parts, used as examples More programming examples (both in printed text and on the CD-ROM) Optimized for the latest Fanuc and related control systems Additional formulas, calculations and handy reference material Fourth axis programming (indexing and rotary) CD-ROM based projects, including several as interactive PDF forms Improved index for better search of topics

Data Science from Scratch: First Principles with Python


Joel Grus - 2015
    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases