Javascript Programming

The Classic Guide to the Java Programming Language--Fully Updated through Java 21 Whatever version of Java you are using, Core Java, Volume I: Fundamentals, Thirteenth Edition, will help you achieve a deep and practical understanding of the language and APIs. With hundreds of realistic examples, Java Champion Cay S. Horstmann demonstrates the most powerful and effective ways to get the job done. Written for experienced programmers looking for in-depth coverage of the Java language and platform, this revised and updated edition continues to be the first choice for serious programmers. The carefully crafted sample programs demonstrate almost every language and library feature, as well as the newest capabilities introduced in Java 21. The examples are purposefully simple to focus on the major points, but, for the most part, they aren't fake and they don't cut corners. They should make good starting points for your own code. This first of two volumes offers a detailed treatment of fundame

《計算機程序設計藝術》系列被公認為計算機科學領域的傑出之作，深入闡述了程序設計理論，對計算機領域的發展有著極為深遠的影響。本卷為系列的第 2卷，講解了半數值算法，分“隨機數”和“算術”兩章。書中總結了主要算法範例及這些算法的基本理論，廣泛剖析了計算機程序設計與數值分析間的相互聯繫。

《傳世經典書叢：UNIX編程藝術》主要介紹了Unix系統領域中的設計和開發哲學、思想文化體系、原則與經驗，由公認的Unix編程大師、開源運動領袖人物之一Eric S.Raymond傾力多年寫作而成。包括Unix設計者在內的多位領域專家也為本書貢獻了寶貴的內容。本書內容涉及社群文化、軟件開發設計與實現，覆蓋面廣、內容深邃，完全展現了作者極其深厚的經驗積累和領域智慧。．

Since its founding by Joseph Papp in the 1950s, The Public Theater has been an American artistic leader defined by its breadth of programming, from Hair and A Chorus Line, to Free Shakespeare in the Park. With the recent critical and financial success of Fun Home and Hamilton , and its emphasis on new play development, The Public’s contemporary history has been equally remarkable, even as world crises and social changes have tested the mettle of its foundation of accessible and “radically inclusive” theatre for all. One Public: New York’s Public Theater in the Era of Oskar Eustis presents the broader organization, its creative methodology, and its enormous growth over the past 20 years. Framed by the tenure and leadership of its current artistic director, the book tells the contemporary story, recorded over many interviews with iconic practitioners and performers ranging from Diane Paulus, Tony Kushner and Lynn Nottage to Kevin Kline, Chelsea Clinton and Lin-Manuel Miranda. C

“Written with grace and intelligence, researched with care. . . . Sure to inspire a new generation of pioneers.” ―Shelf Awareness (starred review)This illuminating biography reveals how the daughter of Lord Byron, Britain’s most infamous Romantic poet, became the world’s first computer programmer.Even by 1800s standards, Ada Byron Lovelace had an unusual upbringing. Her strict mother worked hard at cultivating her own role as the long-suffering ex-wife of bad-boy poet Lord Byron while raising Ada in isolation. Tutored by the brightest minds, Ada developed a hunger for mental puzzles, mathematical conundrums, and scientific discovery that kept pace with the breathtaking advances of the industrial and social revolutions taking place in Europe. At seventeen, Ada met eccentric inventor Charles Babbage, a kindred spirit. Their ensuing collaborations resulted in ideas and concepts that presaged computer programming by almost two hundred years, and Ada Lovelace is now recognized as a pioneer

The endocrine and neuroendocrine system in pregnancy involves highly complex maternal, fetal and placental mechanisms, which are critical for the maintenance of pregnancy, the timing of parturition, for fetal growth and protection from adverse fetal programming. This timely book summarizes the different endocrine aspects related to pregnant women, describing how hormones regulate physiological homeostasis and influence the pathogenesis of disease. The first section of the book covers the role of specific hormones in detail, including oxytocin, hCG and estrogen. The second section discusses gestational disorders such as diabetes, hypertensive disorders and preeclampsia and how the involvement of hormones has clinical implications for management. Best practice for management of endocrine disorders, which can negatively impact pregnancy, such as thyroid disease and obesity, is also reviewed. This book is essential for clinicians and scientists looking to gain knowledge of the role of horm

Understand the theory and implementation of simulation. This book covers simulation topics from a scenario-driven approach using Python and rich visualizations and tabulations. The book discusses simulation used in the natural and social sciences and with simulations taken from the top algorithms used in the industry today. The authors use an engaging approach that mixes mathematics and programming experiments with beginning-intermediate level Python code to create an immersive learning experience that is cohesive and integrated. After reading this book, you will have an understanding of simulation used in natural sciences, engineering, and social sciences using Python. What You Will LearnUse Python and numerical computation to demonstrate the power of simulationChoose a paradigm to run a simulationDraw statistical insights from numerical experimentsKnow how simulation is used to solve real-world problems Who This Book Is ForEntry-level to mid-level Python developers from various backg

Computational thinking is increasingly gaining importance in modern biology, due to the unprecedented scale at which data is nowadays produced. Bridging the cultural gap between the biological and computational sciences, this book serves as an accessible introduction to computational concepts for students in the life sciences. It focuses on teaching algorithmic and logical thinking, rather than just the use of existing bioinformatics tools or programming. Topics are presented from a biological point of view, to demonstrate how computational approaches can be used to solve problems in biology such as biological image processing, regulatory networks, and sequence analysis. The book contains a range of pedagogical features to aid understanding, including real-world examples, in-text exercises, end-of-chapter problems, colour-coded Python code, and 'code explained' boxes. User-friendly throughout, Computational Thinking for Life Scientists promotes the thinking skills and self-efficacy req

Computational thinking is increasingly gaining importance in modern biology, due to the unprecedented scale at which data is nowadays produced. Bridging the cultural gap between the biological and computational sciences, this book serves as an accessible introduction to computational concepts for students in the life sciences. It focuses on teaching algorithmic and logical thinking, rather than just the use of existing bioinformatics tools or programming. Topics are presented from a biological point of view, to demonstrate how computational approaches can be used to solve problems in biology such as biological image processing, regulatory networks, and sequence analysis. The book contains a range of pedagogical features to aid understanding, including real-world examples, in-text exercises, end-of-chapter problems, colour-coded Python code, and 'code explained' boxes. User-friendly throughout, Computational Thinking for Life Scientists promotes the thinking skills and self-efficacy req

A guide to computational thinking education, with a focus on artificial intelligence literacy and the integration of computing and physical objects. Computing has become an essential part of today’s primary and secondary school curricula. In recent years, K–12 computer education has shifted from computer science itself to the broader perspective of computational thinking (CT), which is less about technology than a way of thinking and solving problems―“a fundamental skill for everyone, not just computer scientists,” in the words of Jeanette Wing, author of a foundational article on CT. This volume introduces a variety of approaches to CT in K–12 education, offering a wide range of international perspectives that focus on artificial intelligence (AI) literacy and the integration of computing and physical objects. The book first offers an overview of CT and its importance in K–12 education, covering such topics as the rationale for teaching CT; programming as a general problem-solving

Out of all the ways for young people to learn coding, You Can Code will be the most welcoming, relevant, and fun. Created and authored by best-selling educator Ben Forta, it introduces every basic concept step by step, using projects of gradually increasing complexity. Designed for anyone age 10-17 (or thereabouts), this glossy full-color guide is packed with welcoming images, and powerfully engaging brief text that's extremely easy to understand. All code listings are in full color, with shading to reveal incremental changes, and QR links to short videos with more explanation and examples. Forta teaches with Python, one of today's most powerful and intuitive languages--and every project is a game, covering multiple popular genres. You Can Code makes programming exciting and rewarding, as it prepares a new generation to take their next steps forward--in education, careers, or both.

Machine learning-a computer's ability to learn-is transforming our world: it is used to understand images, process text, make predictions by analyzing large amounts of data, and much more. It can be used in nearly every industry to improve efficiency and help stakeholders make better decisions. Whatever your industry or hobby, chances are that these modern artificial intelligence methods will be useful to you as well.Introduction to Machine Learning weaves reproducible coding examples into explanatory text to show what machine learning is, how it can be applied, and how it works. Perfect for anyone new to the world of AI or those looking to further their understanding, the text begins with a brief introduction to the Wolfram Language, the programming language used for the examples throughout the book. From there, readers are introduced to key concepts before exploring common methods and paradigms such as classification, regression, clustering, and deep learning. The math content is kep

Software testing can be regarded as an art, a craft, and a science. The practical, step-by-step approach presented in this book provides a bridge between these different viewpoints. A single worked example runs throughout, with consistent use of test automation. Each testing technique is introduced in the context of this example, helping students see its strengths and weaknesses. The technique is then explained in more detail, providing a deeper understanding of underlying principles. Finally the limitations of each technique are demonstrated by inserting faults, giving learners concrete examples of when each technique succeeds or fails in finding faults. Coverage includes black-box testing, white-box testing, random testing, unit testing, object-oriented testing, and application testing. The authors also emphasise the process of applying the techniques, covering the steps of analysis, test design, test implementation, and interpretation of results. The book's web site has programming

Benito Mussolini has persistently been described as an 'actor' – and also as a master of illusions. In her vividly narrated account of the Italian dictator's relationship with the theatre, Patricia Gaborik discards any metaphorical notions of Il Duce as a performer and instead tells the story of his life as literal spectator, critic, impresario, dramatist and censor of the stage. Discussing the ways in which the autarch's personal tastes and convictions shaped, in fascist Italy, theatrical programming, she explores Mussolini's most significant dramatic influences, his association with important figures such as Luigi Pirandello, Gabriele D'Annunzio and George Bernard Shaw, his oversight of stage censorship, and his forays into playwriting. By focusing on its subject's manoeuvres in the theatre, and manipulation of theatrical ideas, this consistently illuminating book transforms our understandings of fascism as a whole. It will have strong appeal to readers in both theatre studies and mo

Matrix positivity is a central topic in matrix theory: properties that generalize the notion of positivity to matrices arose from a large variety of applications, and many have also taken on notable theoretical significance, either because they are natural or unifying. This is the first book to provide a comprehensive and up-to-date reference of important material on matrix positivity classes, their properties, and their relations. The matrix classes emphasized in this book include the classes of semipositive matrices, P-matrices, inverse M-matrices, and copositive matrices. This self-contained reference will be useful to a large variety of mathematicians, engineers, and social scientists, as well as graduate students. The generalizations of positivity and the connections observed provide a unique perspective, along with theoretical insight into applications and future challenges. Direct applications can be found in data analysis, differential equations, mathematical programming, compu

Bringing together idiomatic Python programming, foundational numerical methods, and physics applications, this is an ideal standalone textbook for courses on computational physics. All the frequently used numerical methods in physics are explained, including foundational techniques and hidden gems on topics such as linear algebra, differential equations, root-finding, interpolation, and integration. Accompanying the mathematical derivations are full implementations of dozens of numerical methods in Python, as well as more than 250 end-of-chapter problems. Numerical methods and physics examples are clearly separated, allowing this introductory book to be later used as a reference; the penultimate section in each chapter is an in depth project, tackling physics problems which cannot be solved without the use of a computer. Written primarily for students studying computational physics, this textbook brings the non-specialist quickly up to speed with Python before looking in detail at the

There are no silver bullets in algorithm design, and no single algorithmic idea is powerful and flexible enough to solve every computational problem. Nor are there silver bullets in algorithm analysis, as the most enlightening method for analyzing an algorithm often depends on the problem and the application. However, typical algorithms courses rely almost entirely on a single analysis framework, that of worst-case analysis, wherein an algorithm is assessed by its worst performance on any input of a given size. The purpose of this book is to popularize several alternatives to worst-case analysis and their most notable algorithmic applications, from clustering to linear programming to neural network training. Forty leading researchers have contributed introductions to different facets of this field, emphasizing the most important models and results, many of which can be taught in lectures to beginning graduate students in theoretical computer science and machine learning.

Bringing together idiomatic Python programming, foundational numerical methods, and physics applications, this is an ideal standalone textbook for courses on computational physics. All the frequently used numerical methods in physics are explained, including foundational techniques and hidden gems on topics such as linear algebra, differential equations, root-finding, interpolation, and integration. Accompanying the mathematical derivations are full implementations of dozens of numerical methods in Python, as well as more than 250 end-of-chapter problems. Numerical methods and physics examples are clearly separated, allowing this introductory book to be later used as a reference; the penultimate section in each chapter is an in depth project, tackling physics problems which cannot be solved without the use of a computer. Written primarily for students studying computational physics, this textbook brings the non-specialist quickly up to speed with Python before looking in detail at the

Building upon the success of the first edition, Statistics Using Stata uses the latest version of Stata to meet the needs of today's students. Engaging and accessible for students from a variety of mathematical backgrounds, this textbook integrates statistical concepts with the Stata (version 16) software package. It aligns Stata commands with examples based on real data, enabling students to understand statistics in a way that reflects statistical practice. Capitalizing on Stata's menu-driven 'point and click' and program syntax interface, the chapters guide students from the comfortable 'point and click' environment to the beginnings of statistical programming. Its coverage of essential topics gives instructors flexibility in curriculum planning and provides students with more advanced material to prepare for future work. Online resources - including solutions to exercises, PowerPoint slides, and Stata syntax (do-files) for each chapter - allow students to review independently and ad

Finite-state methods are the most efficient mechanisms for analysing textual and symbolic data, providing elegant solutions for an immense number of practical problems in computational linguistics and computer science. This book for graduate students and researchers gives a complete coverage of the field, starting from a conceptual introduction and building to advanced topics and applications. The central finite-state technologies are introduced with mathematical rigour, ranging from simple finite-state automata to transducers and bimachines as 'input-output' devices. Special attention is given to the rich possibilities of simplifying, transforming and combining finite-state devices. All algorithms presented are accompanied by full correctness proofs and executable source code in a new programming language, C(M), which focuses on transparency of steps and simplicity of code. Thus, by enabling readers to obtain a deep formal understanding of the subject and to put finite-state methods t

本書主要針對高中與大學開始接觸程式設計的初學者，及想學好程式設計的讀者所設計。書中文字敘述力求淺顯簡潔，並以大量範例、片語、學習要點、風格要點等方式，逐步引導初學者進入程式設計的領域。二版新增C99語法，如bool類別、顯示位元數整數類別、放寬變數宣告位置、stddef的offsetof及stdlib的二分搜尋bsearch等重點介紹。以更多完整範例、相關圖示說明複雜的觀念與方法，同時強化各範例間

This unique text provides a thorough, yet accessible, grounding in the mathematics, statistics, and programming that students need to master for coursework and research in climate science, meteorology, and oceanography. Assuming only high school mathematics, it presents carefully selected concepts and techniques in linear algebra, statistics, computing, calculus and differential equations within the context of real climate science examples. Computational techniques are integrated to demonstrate how to visualize, analyze, and apply climate data, with R code featured in the book and both R and Python code available online. Exercises are provided at the end of each chapter with selected solutions available to students to aid self-study and further solutions provided online for instructors only. Additional online supplements to aid classroom teaching include datasets, images, and animations. Guidance is provided on how the book can support a variety of courses at different levels, making i

Methods and perspectives to model and measure productivity and efficiency have made a number of important advances in the last decade. Using the standard and innovative formulations of the theory and practice of efficiency and productivity measurement, Robin C. Sickles and Valentin Zelenyuk provide a comprehensive approach to productivity and efficiency analysis, covering its theoretical underpinnings and its empirical implementation, paying particular attention to the implications of neoclassical economic theory. A distinct feature of the book is that it presents a wide array of theoretical and empirical methods utilized by researchers and practitioners who study productivity issues. An accompanying website includes methods, programming codes that can be used with widely available software like MATLAB® and R, and test data for many of the productivity and efficiency estimators discussed in the book. It will be valuable to upper-level undergraduates, graduate students, and professional

Methods and perspectives to model and measure productivity and efficiency have made a number of important advances in the last decade. Using the standard and innovative formulations of the theory and practice of efficiency and productivity measurement, Robin C. Sickles and Valentin Zelenyuk provide a comprehensive approach to productivity and efficiency analysis, covering its theoretical underpinnings and its empirical implementation, paying particular attention to the implications of neoclassical economic theory. A distinct feature of the book is that it presents a wide array of theoretical and empirical methods utilized by researchers and practitioners who study productivity issues. An accompanying website includes methods, programming codes that can be used with widely available software like MATLAB® and R, and test data for many of the productivity and efficiency estimators discussed in the book. It will be valuable to upper-level undergraduates, graduate students, and professional

本書圖文並茂，示例豐富，對C語言的基礎知識進行了徹底剖析，內容涉及輸入輸出、流程控制、數組、函數、指針、文件操作等。對難以理解的概念，均精心繪製示意圖，進行清晰、通俗地講解。本書首次將在線評測系統引入C語言教學，建立了適合初學者的階梯式題庫（http://oj.csoeasy.com/），讓學生在評測過程中取得成就感，培養程序設計的興趣。本書配有豐富的數字資源，包括課程網站（http://www.

Billions have been spent on land conservation but too little attention had been paid to how cost-effective these investments have been. With budgets increasingly constrained, conservationists must learn to fully harness their funds to protect critical resources. Messer and Allen are pioneers in making conservation selection more successful, cost-effective, scientific, and transparent. This book introduces powerful mathematical tools available for project selection, using real-life examples and a practical step-by-step approach. Readers can readily apply these methods to their own work, accomplishing more with less by combining the individual benefits of structured decision-making, mathematical programming, and an understanding of market forces and human behavior. The authors highlight tools from conservation science, mathematics, land use planning and behavioral economics, showing how they can be combined to help protect key environmental resources. This is an invaluable volume for all

Billions have been spent on land conservation but too little attention had been paid to how cost-effective these investments have been. With budgets increasingly constrained, conservationists must learn to fully harness their funds to protect critical resources. Messer and Allen are pioneers in making conservation selection more successful, cost-effective, scientific, and transparent. This book introduces powerful mathematical tools available for project selection, using real-life examples and a practical step-by-step approach. Readers can readily apply these methods to their own work, accomplishing more with less by combining the individual benefits of structured decision-making, mathematical programming, and an understanding of market forces and human behavior. The authors highlight tools from conservation science, mathematics, land use planning and behavioral economics, showing how they can be combined to help protect key environmental resources. This is an invaluable volume for all

本書主要論述了綫性規劃、整數規劃、非綫性規劃、多目標規劃和動態規劃等內容，並介紹了一些成功的實用實例和計算機應用過程，爲便于自學，各章後面都附有習題。本書可作爲高等學校工科專業本科及研究生的教學用書，也可供從事優化研究與應用、現代技術和管理的科技人員參考。

Originally published in 1960, as the second edition of a 1957 original, this textbook is aimed at those without advanced mathematical training and provides a comprehensive introductory account of digital computers, what they are capable of doing and how they are made to do it. It begins with a discussion of programming - the preparation of instructions for the computer. This leads on to a consideration of systems of number storage, from the simple decimal system of desk calculating machines to the varieties of binary storage systems used in modern high-speed computers. The final chapter considers points, which arise in applying computers to engineering calculations, and gives details of some of the problems already solved in this way. Throughout the book the emphasis is on the applications of computers to routine work rather than to advanced research. This book will be of value to students of the history of computer science.

Mathematics is not, and never will be, an empirical science, but mathematicians are finding that the use of computers and specialized software allows the generation of mathematical insight in the form of conjectures and examples, which pave the way for theorems and their proofs. In this way, the experimental approach to pure mathematics is revolutionizing the way research mathematicians work. As the first of its kind, this book provides material for a one-semester course in experimental mathematics that will give students the tools and training needed to systematically investigate and develop mathematical theory using computer programs written in Maple. Accessible to readers without prior programming experience, and using examples of concrete mathematical problems to illustrate a wide range of techniques, the book gives a thorough introduction to the field of experimental mathematics, which will prepare students for the challenge posed by open mathematical problems.

Maple is a powerful symbolic computation system that is widely used in universities around the world. This short introduction gives readers an insight into the rules that control how the system works, and how to understand, fix, and avoid common problems. Topics covered include algebra, calculus, linear algebra, graphics, programming, and procedures. Each chapter contains numerous illustrative examples, using mathematics that does not extend beyond first-year undergraduate material. Maple worksheets containing these examples are available for download from the author's personal website. The book is suitable for new users, but where advanced topics are central to understanding Maple they are tackled head-on. Many concepts which are absent from introductory books and manuals are described in detail. With this book, students, teachers and researchers will gain a solid understanding of Maple and how to use it to solve complex mathematical problems in a simple and efficient way.

Data structures are the fundamental building blocks of any computer program, used for storing, representing and manipulating data in a computer. This text presents the basic concepts of data structures as part of the art of writing computer programs. The author concentrates on the fundamentals of what should be done to solve a problem efficiently rather than technical implementation details. The text includes pseudocode and covers all the most common data structures, such as queues, stacks, trees, heaps, and hash tables, along with the basics of searching, sorting, and coding. This book can supplement any undergraduate algorithms or discrete math course and will also be accessible to students and researchers in other quantitative disciplines. No prerequisites beyond introductory programming and basic mathematics are required, and the accessible, conceptual presentation will appeal to undergraduates in many quantitative fields. Carefully designed problem sets with selected solutions wil

Data structures are the fundamental building blocks of any computer program, used for storing, representing and manipulating data in a computer. This text presents the basic concepts of data structures as part of the art of writing computer programs. The author concentrates on the fundamentals of what should be done to solve a problem efficiently rather than technical implementation details. The text includes pseudocode and covers all the most common data structures, such as queues, stacks, trees, heaps, and hash tables, along with the basics of searching, sorting, and coding. This book can supplement any undergraduate algorithms or discrete math course and will also be accessible to students and researchers in other quantitative disciplines. No prerequisites beyond introductory programming and basic mathematics are required, and the accessible, conceptual presentation will appeal to undergraduates in many quantitative fields. Carefully designed problem sets with selected solutions wil

本書從應用程式設計的角度解釋x86處理器的內部架構和執行環境，全面介紹如何用x86組合語言編寫可被高階語言調用的函數。主要內容包括：x86-32核心架構（第1章和第2章），x87浮點單元（第3章和第4章），MMX技術（第5章和第6章），流式SIMD擴展（第7章至第11章），高級向量擴展（第12章至第16章），x86-64核心架構（第17章和第18章），x86-64SSE和AVX（第19章和第20章

本書作者就是 15 年前編寫了 Programming Ruby，將 Ruby 帶入大眾視野的 Dave Thomas。這一次他延續了一貫的寫作風格，以一個擁有物件導向的開發經歷但並未接觸過函數式程式設計的開發者的角度切入，循序漸進地帶領讀者進入 Elixir 的奇妙世界。通過一步步的實驗探索，引導讀者逐步跳出已有的程式設計思維模式，以全新的函數式程式設計方式來思考及尋找解決實際問題的辦法。然而本

Storytelling is a fundamental mode of everyday interaction. This book is based upon the Narrative Corpus (NC), a specialized corpus of naturally occurring narratives, and provides new paths for its study. Christoph Rühlemann uses the NC's narrative-specific annotation and XPath and XQuery, query languages that allow the retrieval of complex data structures, to facilitate large-scale quantitative investigations into how narrators and recipients collaborate in storytelling. Empirical analyses are validated using R, a programming language and environment for statistical computing and graphics. Using this unique data and methodological base, Rühlemann reveals new insights, including the discovery of turntaking patterns specific to narrative, the first investigation of textual colligation in spoken data, the unearthing of how speech reports, as discourse units, form striking patterns at utterance level, and the identification of the story climax as the sequential context in which recipient

Software is pervasive in our lives. We are accustomed to dealing with the failures of much of that software - restarting an application is a very familiar solution. Such solutions are unacceptable when the software controls our cars, airplanes and medical devices or manages our private information. These applications must run without error. SPARK provides a means, based on mathematical proof, to guarantee that a program has no errors. SPARK is a formally defined programming language and a set of verification tools specifically designed to support the development of software used in high integrity applications. Using SPARK, developers can formally verify properties of their code such as information flow, freedom from runtime errors, functional correctness, security properties and safety properties. Written by two SPARK experts, this is the first introduction to the just-released 2014 version. It will help students and developers alike master the basic concepts for building systems with

Software is pervasive in our lives. We are accustomed to dealing with the failures of much of that software - restarting an application is a very familiar solution. Such solutions are unacceptable when the software controls our cars, airplanes and medical devices or manages our private information. These applications must run without error. SPARK provides a means, based on mathematical proof, to guarantee that a program has no errors. SPARK is a formally defined programming language and a set of verification tools specifically designed to support the development of software used in high integrity applications. Using SPARK, developers can formally verify properties of their code such as information flow, freedom from runtime errors, functional correctness, security properties and safety properties. Written by two SPARK experts, this is the first introduction to the just-released 2014 version. It will help students and developers alike master the basic concepts for building systems with

這不是第一本關於NLP的書，卻是第一本讓你身臨其境迅速掌握NLP精髓的書！喬的生活又一次陷入了困境，工作上遇到了麻煩，女朋友也和他鬧彆扭。一年前的一次NLP課程，曾經啟發過迷惑的他。現在，他帶著沮喪的心情再次走進NLP大師理查·班德勒的研習班。這次課程，能令喬的生活重現生機嗎？他能在這裡遇見更好的自己嗎？NLP（Neuro-Linguistic Programming，神經語言程式學）是一門複製卓

The majority of empirical research in economics ignores the potential benefits of nonparametric methods, while the majority of advances in nonparametric theory ignore the problems faced in applied econometrics. This book helps bridge this gap between applied economists and theoretical nonparametric econometricians. It discusses in depth, and in terms that someone with only one year of graduate econometrics can understand, basic to advanced nonparametric methods. The analysis starts with density estimation and motivates the procedures through methods that should be familiar to the reader. It then moves on to kernel regression, estimation with discrete data, and advanced methods such as estimation with panel data and instrumental variables models. The book pays close attention to the issues that arise with programming, computing speed, and application. In each chapter, the methods discussed are applied to actual data, paying attention to presentation of results and potential pitfalls.