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Mathematical Statistics for Economics and Business
Mathematical Statistics for Economics and Business

Mathematical Statistics for Economics and Business, Second Edition, provides a comprehensive introduction to the principles of mathematical statistics which underpin statistical analyses in the fields of economics, business, and econometrics.  The selection of topics in this textbook is designed to provide students with a...

Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB
Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB
Engineering disciplines are those fields of research and development that attempt to create products and systems operating in, and dealing with, the real world. The number of disciplines is large, as is the range of scales that they typically operate in: from the very small scale of nanotechnology up to very large scales that span whole regions,...
A Probability Path (Modern Birkhäuser Classics)
A Probability Path (Modern Birkhäuser Classics)

Many probability books are written by mathematicians and have the built-in bias that the reader is assumed to be a mathematician coming to the material for its beauty. This textbook is geared towards beginning graduate students from a variety of disciplines whose primary focus is not necessarily mathematics for its own sake. Instead,...

An Invitation to 3-D Vision: From Images to Geometric Models (Interdisciplinary Applied Mathematics)
An Invitation to 3-D Vision: From Images to Geometric Models (Interdisciplinary Applied Mathematics)
This book is intended to give students at the advanced undergraduate or introductory graduate level, and researchers in computer vision, robotics and computer graphics, a self-contained introduction to the geometry of three-dimensional (3- D) vision. This is the study of the reconstruction of 3-D models of objects from a...
Bayesian Brain: Probabilistic Approaches to Neural Coding (Computational Neuroscience)
Bayesian Brain: Probabilistic Approaches to Neural Coding (Computational Neuroscience)

A Bayesian approach can contribute to an understanding of the brain on multiple levels, by giving normative predictions about how an ideal sensory system should combine prior knowledge and observation, by providing mechanistic interpretation of the dynamic functioning of the brain circuit, and by suggesting optimal ways of deciphering...

2D Object Detection and Recognition: Models, Algorithms, and Networks
2D Object Detection and Recognition: Models, Algorithms, and Networks
This book is about detecting and recognizing 2D objects in gray-level images. Howare
models constructed? Howare they trained? What are the computational approaches to
efficient implementation on a computer? And finally, how can some of these computations
be implemented in the framework of parallel and biologically plausible neural...
Bayesian Biostatistics and Diagnostic Medicine
Bayesian Biostatistics and Diagnostic Medicine
Bayesian methods are being used more often than ever before in biology and medicine. For example, at the University of Texas MD Anderson Cancer Center, Bayesian sequential stopping rules routinely are used for the design of clinical trials. This book is based on the author’s experience working with a variety of...
Statistical Methods, Second Edition
Statistical Methods, Second Edition

This broad text provides a complete overview of most standard statistical methods, including multiple regression, analysis of variance, experimental design, and sampling techniques. Assuming a background of only two years of high school algebra, this book teaches intelligent data analysis and covers the principles of good data collection....

Statistical Pattern Recognition
Statistical Pattern Recognition

Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract information and make justified decisions. It is a very active area of study and research, which has seen many advances in recent years. Applications such as data mining, web searching, multimedia data retrieval,...

Think Bayes
Think Bayes

If you know how to program with Python and also know a little about probability, you’re ready to tackle Bayesian statistics. With this book, you'll learn how to solve statistical problems with Python code instead of mathematical notation, and use discrete probability distributions instead of continuous mathematics. Once you...

Advanced Digital Signal Processing and Noise Reduction
Advanced Digital Signal Processing and Noise Reduction
Signal processing plays an increasingly central role in the development of modern telecommunication and information processing systems, with a wide range of applications in areas such as multimedia technology, audio-visual signal processing, cellular mobile communication, radar systems and financial data forecasting. The theory and application of...
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...
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