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TikZ Cookbook for Diagram in Economics

Author: Chiu Yu Ko

Publisher: Chiu Yu Ko

Published:

Total Pages: 629

ISBN-13:

Economists present their arguments in three different types of arguments: verbal, graphical, and mathematical. If you flip over introductory economic textbooks, you will notice that analysis is usually done based on verbal argument and diagrams. Even for intermediate and advanced textbooks, you will notice that the difference is the mathematical argument -- diagrams are still useful. This is also true for academic research. However, drawing a nice diagram is not easy. Standard software is not good for drawing economic diagrams. Either it is too simple or it is too professional. One nice drawing software is the TikZ package in LaTeX . However, it is a drawing programming so that there is a steep learning curve. This is the reason that I write this book.

TikZ Cookbook for Diagram in Economics Companion

Author: Chiu Yu Ko

Publisher: Chiu Yu Ko

Published:

Total Pages: 307

ISBN-13:

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This book is the first companion book for "TikZ Cookbook for Diagram in Economics: step-by-step illustration". It illustrates how to draw economic diagrams found in the popular principle of economics textbook using TikZ. If you want to download the code tex file, you may buy here: https://gumroad.com/l/ljVrJ

R Markdown Cookbook

Author: Yihui Xie

Publisher: CRC Press

Published: 2020-10-21

Total Pages: 353

ISBN-13: 1000290883

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This new book written by the developers of R Markdown is an essential reference that will help users learn and make full use of the software. Those new to R Markdown will appreciate the short, practical examples that address the most common issues users encounter. Frequent users will also benefit from the wide ranging tips and tricks that expose ‘hidden’ features, support customization and demonstrate the many new and varied applications of the software. After reading this book users will learn how to: Enhance your R Markdown content with diagrams, citations, and dynamically generated text Streamline your workflow with child documents, code chunk references, and caching Control the formatting and layout with Pandoc markdown syntax or by writing custom HTML and LaTeX templates Utilize chunk options and hooks to fine-tune how your code is processed Switch between different language engineers to seamlessly incorporate python, D3, and more into your analysis

Practical Handbook for Small-Gauge Vitrectomy

Author: Ulrich Spandau

Publisher: Springer

Published: 2018-08-22

Total Pages: 382

ISBN-13: 3319896776

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Since publication of the first edition of this book in 2012 vitreoretinal surgery has marched with huge steps forward. In 2012 23G was standard, today 25G and 27G are the most commonly used gauge sizes for vitrectomy. In 2012 the cutting rate was 5.000 cuts/min and today with the development of a novel vitreous cutter the cutting rate has increased to 16.000 cuts/min. The advent of 25G/27G made the instruments smaller and surgery less traumatic. Practical Handbook for Small-Gauge Vitrectomy: A Step-By-Step Introduction to Surgical Techniques, 2ndEdition focuses on these new developments and features new chapters on PVR detachment, intraocular tumour, macular translocation, sub macular hemorrhages and ocular trauma. The surgeries are demonstrated step-by-step and the material is shown in detail and videos visualize the surgery.This book will serve as an immensely useful guide for all surgeons who are intending to make use of this exciting and increasingly used technique.

TikZ Cookbook for Diagram in Economics Companion

Author: Chiu Yu Ko

Publisher: Chiu Yu Ko

Published:

Total Pages:

ISBN-13:

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This book is the second companion book for "TikZ Cookbook for Diagram in Economics: step-by-step illustration". It illustrates how to draw economic diagrams found in the intermediate microeconomics textbook using TikZ.

Doing Bayesian Data Analysis

Author: John Kruschke

Publisher: Academic Press

Published: 2010-11-25

Total Pages: 673

ISBN-13: 0123814863

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There is an explosion of interest in Bayesian statistics, primarily because recently created computational methods have finally made Bayesian analysis tractable and accessible to a wide audience. Doing Bayesian Data Analysis, A Tutorial Introduction with R and BUGS, is for first year graduate students or advanced undergraduates and provides an accessible approach, as all mathematics is explained intuitively and with concrete examples. It assumes only algebra and ‘rusty’ calculus. Unlike other textbooks, this book begins with the basics, including essential concepts of probability and random sampling. The book gradually climbs all the way to advanced hierarchical modeling methods for realistic data. The text provides complete examples with the R programming language and BUGS software (both freeware), and begins with basic programming examples, working up gradually to complete programs for complex analyses and presentation graphics. These templates can be easily adapted for a large variety of students and their own research needs.The textbook bridges the students from their undergraduate training into modern Bayesian methods. Accessible, including the basics of essential concepts of probability and random sampling Examples with R programming language and BUGS software Comprehensive coverage of all scenarios addressed by non-bayesian textbooks- t-tests, analysis of variance (ANOVA) and comparisons in ANOVA, multiple regression, and chi-square (contingency table analysis). Coverage of experiment planning R and BUGS computer programming code on website Exercises have explicit purposes and guidelines for accomplishment

Big Data Analytics

Author: Kim H. Pries

Publisher: CRC Press

Published: 2015-02-05

Total Pages: 576

ISBN-13: 1482234521

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With this book, managers and decision makers are given the tools to make more informed decisions about big data purchasing initiatives. Big Data Analytics: A Practical Guide for Managers not only supplies descriptions of common tools, but also surveys the various products and vendors that supply the big data market.Comparing and contrasting the dif

Achtung-Panzer!

Author: Heinz Guderian

Publisher: Arms & Armour

Published: 1995

Total Pages: 220

ISBN-13: 9781854092823

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This is one of the most significant military books of the twentieth century. By an outstanding soldier of independent mind, it pushed forward the evolution of land warfare and was directly responsible for German armoured supremacy in the early years of the Second World War. Published in 1937, the result of 15 years of careful study since his days on the German General Staff in the First World War, Guderian's book argued, quite clearly, how vital the proper use of tanks and supporting armoured vehicles would be in the conduct of a future war. When that war came, just two years later, he proved it, leading his Panzers with distinction in the Polish, French and Russian campaigns. Panzer warfare had come of age, exactly as he had forecast. This first English translation of Heinz Guderian's classic book - used as a textbook by Panzer officers in the war - has an introduction and extensive background notes by the modern English historian Paul Harris.

LaTeX and Friends

Author: M. R. C. van Dongen

Publisher: Springer Science & Business Media

Published: 2012-01-28

Total Pages: 313

ISBN-13: 3642238165

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LaTeX is a free, automated state-of-the-art typesetting system. This book teaches all the ins and outs of LaTeX which are needed to write an article, report, thesis, or book. The book teaches by example, giving many worked out examples showing input and output side by side. The book presents the most recent techniques for presenting data plots, complex graphics, and computer presentations, but does not require previous knowledge. However, it is also a reference for the more seasoned user, with pointers to modern techniques and packages. Recurring themes in the book are consistent and effective presentation, planning and development, controlling style and content, and maintenance.

Doing Bayesian Data Analysis

Author: John Kruschke

Publisher: Academic Press

Published: 2014-11-11

Total Pages: 776

ISBN-13: 0124059163

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Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan, Second Edition provides an accessible approach for conducting Bayesian data analysis, as material is explained clearly with concrete examples. Included are step-by-step instructions on how to carry out Bayesian data analyses in the popular and free software R and WinBugs, as well as new programs in JAGS and Stan. The new programs are designed to be much easier to use than the scripts in the first edition. In particular, there are now compact high-level scripts that make it easy to run the programs on your own data sets. The book is divided into three parts and begins with the basics: models, probability, Bayes’ rule, and the R programming language. The discussion then moves to the fundamentals applied to inferring a binomial probability, before concluding with chapters on the generalized linear model. Topics include metric-predicted variable on one or two groups; metric-predicted variable with one metric predictor; metric-predicted variable with multiple metric predictors; metric-predicted variable with one nominal predictor; and metric-predicted variable with multiple nominal predictors. The exercises found in the text have explicit purposes and guidelines for accomplishment. This book is intended for first-year graduate students or advanced undergraduates in statistics, data analysis, psychology, cognitive science, social sciences, clinical sciences, and consumer sciences in business. Accessible, including the basics of essential concepts of probability and random sampling Examples with R programming language and JAGS software Comprehensive coverage of all scenarios addressed by non-Bayesian textbooks: t-tests, analysis of variance (ANOVA) and comparisons in ANOVA, multiple regression, and chi-square (contingency table analysis) Coverage of experiment planning R and JAGS computer programming code on website Exercises have explicit purposes and guidelines for accomplishment Provides step-by-step instructions on how to conduct Bayesian data analyses in the popular and free software R and WinBugs