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Learning R for Geospatial Analysis
Learning R for Geospatial Analysis

R is a simple, effective, and comprehensive programming language and environment that is gaining ever-increasing popularity among data analysts. This book provides you with the necessary skills to successfully carry out complete geospatial data analyses, from data import to presentation of results. Learning R for Geospatial Analysis is composed of step-by-step tutorials, starting with the language basics before proceeding to cover the main GIS operations and data types. Visualization of spatial data is vital either during the various analysis steps and/or as the final product, and this book shows you how to get the most out of R's visualization capabilities. The book culminates with examples of cutting-edge applications utilizing R's strengths as a statistical and graphical tool. ...
Beginning OpenOffice Calc
Beginning OpenOffice Calc

OpenOffice Calc is the most powerful and widespread open source spreadsheet application in existence. It is the only real alternative to Excel. Jacek Artymiak is widely regarded as the authority on OpenOffice Calc. He takes you, step by step, from the interface and handling Calc files to working with data sources small and large. Artymiak then extends the reader's skillset to data visualization, writing complex formulas and performing statistical analysis. Beginning OpenOffice Calc allows you to gain confidence in the considered use of statistical formulas, but does not assume familiarity with another spreadsheet application. ...
R Quick Syntax Reference
R Quick Syntax Reference

The R Quick Syntax Reference is a handy reference book detailing the intricacies of the R language. Not only is R a free, open-source tool, R is powerful, flexible, and has state of the art statistical techniques available. With the many details which must be correct when using any language, however, the R Quick Syntax Reference makes using R easier. Starting with the basic structure of R, the book takes you on a journey through the terminology used in R and the syntax required to make R work. You will find looking up the correct form for an expression quick and easy. With a copy of the R Quick Syntax Reference in hand, you will find that are able to use the multitude of functions available to the R user and are even able to write your own functions to explore and analyze data. ...
Practical Methods of Financial Engineering and Risk Management
Practical Methods of Financial Engineering and Risk Management

Risk control, capital allocation, and realistic derivative pricing and hedging are critical concerns for major financial institutions and individual traders alike. Events from the collapse of Lehman Brothers to the Greek sovereign debt crisis demonstrate the urgent and abiding need for statistical tools adequate to measure and anticipate the amplitude of potential swings in the financial markets - from ordinary stock price and interest rate moves, to defaults, to those increasingly frequent "rare events" fashionably called black swan events. Yet many on Wall Street continue to rely on standard models based on artificially simplified assumptions that can lead to systematic (and sometimes catastrophic) underestimation of real risks. ...
MATLAB Graphical Programming
MATLAB Graphical Programming

MATLAB enables you to work with its graphics capabilities in almost all areas of the experimental sciences and engineering. The commands that MATLAB implements in job related graphics are quite useful and are very efficient. MATLAB has functions for working with two-dimensional and three-dimensional graphics, statistical graphs, curves and surfaces in explicit, implicit, parametric and polar coordinates. It also works perfectly with twisted curves, surfaces, volumes and graphical interpolation. This book is for those who deal in graphics at many levels wanting to graph and analyze the functions / problems graphically. ...
Regression Analysis by Example, 5th Edition
Regression Analysis by Example, 5th Edition

Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. Regression Analysis by Example, Fifth Edition has been expanded and thoroughly updated to reflect recent advances in the field. The emphasis continues to be on exploratory data analysis rather than statistical theory. The book offers in-depth treatment of regression diagnostics, transformation, multicollinearity, logistic regression, and robust regression. The book now includes a new chapter on the detection and correction of multicollinearity, while also showcasing the use of the discussed methods on newly added data sets from the fields of engineering, medicine, and business. ...
Introduction to R for Quantitative Finance
Introduction to R for Quantitative Finance

Introduction to R for Quantitative Finance will show you how to solve real-world quantitative fi nance problems using the statistical computing language R. The book covers diverse topics ranging from time series analysis to fi nancial networks. Each chapter briefl y presents the theory behind specific concepts and deals with solving a diverse range of problems using R with the help of practical examples. This book will be your guide on how to use and master R in order to solve quantitative finance problems. This book covers the essentials of quantitative finance, taking you through a number of clear and practical examples in R that will not only help you to understand the theory, but how to effectively deal with your own real-life problems. ...
Instant R Starter
Instant R Starter

R is a versatile cross-platform environment with the power of a programming language and the flexibility of a scripting language. It is extremely powerful in manipulating and visualizing complex databases, performing statistical computations and producing any kind of plot with a very high graphical quality. Instant R Starter is a practical introduction to the R language and will show you how to use the main functionalities of the environment. It has hands-on instructions on data analysis, data manipulation, and tips and tricks on quickly debugging your programs. ...
Advanced Analytics with Spark
Advanced Analytics with Spark

In this practical book, four Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark. The authors bring Spark, statistical methods, and real-world data sets together to teach you how to approach analytics problems by example. You'll start with an introduction to Spark and its ecosystem, and then dive into patterns that apply common techniques - classification, collaborative filtering, and anomaly detection among others - to fields such as genomics, security, and finance. If you have an entry-level understanding of machine learning and statistics, and you program in Java, Python, or Scala, you'll find these patterns useful for working on your own data applications. ...
Mastering Python for Finance
Mastering Python for Finance

Built initially for scientific computing, Python quickly found its place in finance. Its flexibility and robustness can be easily incorporated into applications for mathematical studies, research, and software development. With this book, you will learn about all the tools you need to successfully perform research studies and modeling, improve your trading strategies, and effectively manage risks. You will explore the various tools and techniques used in solving complex problems commonly faced in finance. You will learn how to price financial instruments such as stocks, options, interest rate derivatives, and futures using computational methods. Also, you will learn how you can perform data analytics on market indexes and use NoSQL to store tick data. ...
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