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Matlab for Engineers
Matlab for Engineers

This book grew out of my experience teaching MATLAB® and other computing languages to freshmen engineering students at Salt Lake Community College. I was frustrated by the lack of a text that “started at the beginning.” Although there were many comprehensive reference books, they assumed a level of both mathematical and...

Kernel Smoothing: Principles, Methods and Applications
Kernel Smoothing: Principles, Methods and Applications

Comprehensive theoretical overview of kernel smoothing methods with motivating examples

Kernel smoothing is a flexible nonparametric curve estimation method that is applicable when parametric descriptions of the data are not sufficiently adequate. This book explores theory and methods of kernel smoothing in a variety of...

Multivariate Time Series Analysis: With R and Financial Applications
Multivariate Time Series Analysis: With R and Financial Applications

An accessible guide to the multivariate time series tools used in numerous real-world applications

Multivariate Time Series Analysis: With R and Financial Applications is the much anticipated sequel coming from one of the most influential and prominent experts on the topic of time series. Through a...

Statistical Computing in C++ and R (Chapman & Hall/CRC The R Series)
Statistical Computing in C++ and R (Chapman & Hall/CRC The R Series)

With the advancement of statistical methodology inextricably linked to the use of computers, new methodological ideas must be translated into usable code and then numerically evaluated relative to competing procedures. In response to this, Statistical Computing in C++ and R concentrates on the writing of code rather...

Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery (Use R!)
Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery (Use R!)
Data Mining and Anlaytics are the foundation technologies for the new knowledge based world where we build models from data and databases to understand and explore our world. Data mining can improve our business, improve our government, and improve our life and with the right tools, any one can begin to explore this new technology, on the path...
R Through Excel: A Spreadsheet Interface for Statistics, Data Analysis, and Graphics (Use R!)
R Through Excel: A Spreadsheet Interface for Statistics, Data Analysis, and Graphics (Use R!)

In this book, the authors build on RExcel, a free add-in for Excel that can be downloaded from the R distribution network. RExcel seamlessly integrates the entire set of R's statistical and graphical methods into Excel, allowing students to focus on statistical methods and concepts and minimizing the distraction of learning a new...

Probability: With Applications and R
Probability: With Applications and R

An introduction to probability at the undergraduate level

Chance and randomness are encountered on a daily basis. Authored by a highly qualified professor in the field, Probability: With Applications and R delves into the theories and applications essential to obtaining a thorough understanding of probability.

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Inference Control in Statistical Databases: From Theory to Practice (Lecture Notes in Computer Science)
Inference Control in Statistical Databases: From Theory to Practice (Lecture Notes in Computer Science)
Inference control in statistical databases, also known as statistical disclosure limitation or statistical confidentiality, is about finding tradeoffs to the tension between the increasing societal need for accurate statistical data and the legal and ethical obligation to protect privacy of individuals and enterprises which are the source...
Data Mining: Concepts, Models, Methods, and Algorithms, Second Edition
Data Mining: Concepts, Models, Methods, and Algorithms, Second Edition
Now updated—the systematic introductory guide to modern analysis of large data sets

As data sets continue to grow in size and complexity, there has been an inevitable move towards indirect, automatic, and intelligent data analysis in which the analyst works via more complex and sophisticated software tools. This book...

Java for Data Science
Java for Data Science
Examine the techniques and Java tools supporting the growing field of data science About This Book Your entry ticket to the world of data science with the stability and power of Java Explore, analyse, and visualize your data effectively using easy-to-follow examples Make your Java applications more capable using machine learning Who This Book Is...
Sampling Algorithms (Springer Series in Statistics)
Sampling Algorithms (Springer Series in Statistics)
This book is based upon courses on sampling algorithms. After having used scattered notes for several years, I have decided to completely rewrite the material in a consistent way. The books of Brewer and Hanif (1983) and H´ajek (1981) have been my works of reference. Brewer and Hanif (1983) have drawn up an...
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)

This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of colour graphics. It is a valuable resource...

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