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The Statistics of Gene Mapping (Statistics for Biology and Health)
The Statistics of Gene Mapping (Statistics for Biology and Health)

This book details the statistical concepts used in gene mapping, first in the experimental context of crosses of inbred lines and then in outbred populations, primarily humans. It presents elementary principles of probability and statistics, which are implemented by computational tools based on the R programming language to simulate genetic...

The Mathematics of Signal Processing (Cambridge Texts in Applied Mathematics)
The Mathematics of Signal Processing (Cambridge Texts in Applied Mathematics)

Arising from courses taught by the authors, this largely self-contained treatment is ideal for mathematicians who are interested in applications or for students from applied fields who want to understand the mathematics behind their subject. Early chapters cover Fourier analysis, functional analysis, probability and linear algebra, all of...

Data Science from Scratch: First Principles with Python
Data Science from Scratch: First Principles with Python

Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from...

Doing Data Science: Straight Talk from the Frontline
Doing Data Science: Straight Talk from the Frontline

Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to...

R in a Nutshell (In a Nutshell (O'Reilly))
R in a Nutshell (In a Nutshell (O'Reilly))

If you’re considering R for statistical computing and data visualization, this book provides a quick and practical guide to just about everything you can do with the open source R language and software environment. You’ll learn how to write R functions and use R packages to help you prepare, visualize, and analyze data....

Random Matrix Methods for Wireless Communications
Random Matrix Methods for Wireless Communications

Blending theoretical results with practical applications, this book provides an introduction to random matrix theory and shows how it can be used to tackle a variety of problems in wireless communications. The Stieltjes transform method, free probability theory, combinatoric approaches, deterministic equivalents and spectral analysis methods...

Statistics in a Nutshell
Statistics in a Nutshell

Need to learn statistics for your job? Want help passing a statistics course? Statistics in a Nutshell is a clear and concise introduction and reference for anyone new to the subject. Thoroughly revised and expanded, this edition helps you gain a solid understanding of statistics without the numbing complexity of many college...

Stochastic Systems: Uncertainty Quantification and Propagation (Springer Series in Reliability Engineering)
Stochastic Systems: Uncertainty Quantification and Propagation (Springer Series in Reliability Engineering)

Uncertainty is an inherent feature of both properties of physical systems and the inputs to these systems that needs to be quantified for cost effective and reliable designs. The states of these systems satisfy equations with random entries, referred to as stochastic equations, so that they are random functions of time and/or space. The...

Surveillance and Threat Detection: Prevention versus Mitigation
Surveillance and Threat Detection: Prevention versus Mitigation

Surveillance and Threat Detection offers readers a complete understanding of the terrorist/criminal cycle, and how to interrupt that cycle to prevent an attack.

Terrorists and criminals often rely on pre-attack and pre-operational planning and surveillance activities that can last a period of weeks, months, or even years....

Modeling and Convexity (Iste)
Modeling and Convexity (Iste)

This reference book gives the reader a complete but comprehensive presentation of the foundations of convex analysis and presents applications to significant situations in engineering. The presentation of the theory is self-contained and the proof of all the essential results is given. The examples consider meaningful situations such as the...

Random Processes by Example
Random Processes by Example

This volume first introduces the mathematical tools necessary for understanding and working with a broad class of applied stochastic models. The toolbox includes Gaussian processes, independently scattered measures such as Gaussian white noise and Poisson random measures, stochastic integrals, compound Poisson, infinitely divisible and stable...

Approximate Iterative Algorithms
Approximate Iterative Algorithms

Iterative algorithms often rely on approximate evaluation techniques, which may include statistical estimation, computer simulation or functional approximation. This volume presents methods for the study of approximate iterative algorithms, providing tools for the derivation of error bounds and convergence rates, and for the optimal design of...

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