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Parameter Estimation for Scientists and Engineers
Parameter Estimation for Scientists and Engineers
The subject of this book is estimating parameters of expectation models of statistical observations. The book describes what I consider the most important aspects of the subject for applied scientists and engineers. From experience, I know that this group of users is often not aware of estimators other than least squares. Therefore, one of my...
COMPSTAT 2006 - Proceedings in Computational Statistics: 17th Symposium Held in Rome, Italy, 2006
COMPSTAT 2006 - Proceedings in Computational Statistics: 17th Symposium Held in Rome, Italy, 2006
The book provides new developments in data analysis and statistical multivariate methods, computational statistics and algorithms, including new topics which are of central interest to modern statistics. The reader will find advanced methodologies and computational methods which are very helpful to analyze real phenomena characterized by large data...
Schaum's Outline of Mathematica, 2ed (Schaum's Outline Series)
Schaum's Outline of Mathematica, 2ed (Schaum's Outline Series)
Master Mathematica with Schaum's, the high-performance study guide. It will help you cut study time, hone problem-solving skills, and achieve your personal best on exams and projects!

Students love Schaum's Outlines because they produce results. Each year, hundreds of thousands of students improve their test scores and final grades with these...

Applied Data Mining: Statistical Methods for Business and Industry
Applied Data Mining: Statistical Methods for Business and Industry

"…a book with many nice features that has elements of interest for …every subset of the intended audience…"
 (Journal of the American Statistical Association, September 2006)

"The author's style is consistently readable. Stripping out all but the barest essential...

The Blender Python API: Precision 3D Modeling and Add-on Development
The Blender Python API: Precision 3D Modeling and Add-on Development

Understand Blender's Python API to allow for precision 3D modeling and add-on development. Follow detailed guidance on how to create precise geometries, complex texture mappings, optimized renderings, and much more.

This book is a detailed, user-friendly guide to understanding and using Blender’s Python API for...

Exploratory Multivariate Analysis by Example Using R (Chapman & Hall/CRC Computer Science & Data Analysis)
Exploratory Multivariate Analysis by Example Using R (Chapman & Hall/CRC Computer Science & Data Analysis)

Full of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R focuses on four fundamental methods of multivariate exploratory data analysis that are most suitable for applications. It covers principal component analysis (PCA) when variables are quantitative, correspondence analysis...

Advanced Web Metrics with Google Analytics
Advanced Web Metrics with Google Analytics

How Does Your Website Measure Up?

Are you getting the most out of your website? Google insider and web metrics expert Brian Clifton reveals the information you need to get a true picture of your site's impact and stay competitive using Google Analytics (GA) and the latest web metrics methodologies.

...

Intelligent Systems: Approximation by Artificial Neural Networks (Intelligent Systems Reference Library)
Intelligent Systems: Approximation by Artificial Neural Networks (Intelligent Systems Reference Library)

This brief monograph is the first one to deal exclusively with the quantitative approximation by artificial neural networks to the identity-unit operator. Here we study with rates the approximation properties of the "right" sigmoidal and hyperbolic tangent artificial neural network positive linear operators. In particular we study...

Adaptive Learning of Polynomial Networks: Genetic Programming, Backpropagation and Bayesian Methods
Adaptive Learning of Polynomial Networks: Genetic Programming, Backpropagation and Bayesian Methods

This book delivers theoretical and practical knowledge for developing algorithms that infer linear and non-linear multivariate models, providing a methodology for inductive learning of polynomial neural network models (PNN) from data. The text emphasizes an organized model identification process by which to discover models that generalize and...

Applied Data Mining for Business and Industry
Applied Data Mining for Business and Industry

The increasing availability of data in our current, informationoverloaded society has led to the need for valid tools for itsmodelling and analysis. Data mining and applied statistical methodsare the appropriate tools to extract knowledge from such data. Thisbook provides an accessible introduction to data mining methods ina consistent and...

Software Reliability Modeling: Fundamentals and Applications (SpringerBriefs in Statistics)
Software Reliability Modeling: Fundamentals and Applications (SpringerBriefs in Statistics)

Software reliability is one of the most important characteristics of software product quality. Its measurement and management technologies during the software product life cycle are essential to produce and maintain quality/reliable software systems. Part 1 of this book introduces several aspects of software reliability modeling and its...

Advances in Data Analysis: Proceedings of the 30th Annual Conference
Advances in Data Analysis: Proceedings of the 30th Annual Conference
The book focuses on exploratory data analysis, learning of latent structures in datasets, and unscrambling of knowledge. It covers a broad range of methods from multivariate statistics, clustering and classification, visualization and scaling as well as from data and time series analysis. It provides new approaches for information retrieval and...
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