A state-of-the-art introduction to the powerful mathematical and statistical tools used in the field of finance

The use of mathematical models and numerical techniques is a practice employed by a growing number of applied mathematicians working on applications in finance. Reflecting this development, Numerical Methods in Finance and Economics: A MATLAB?-Based Introduction, Second Edition bridges the gap between financial theory and computational practice while showing readers how to utilize MATLAB?--the powerful numerical computing environment--for financial applications.
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The statistical methods and techniques described in this text range from descriptive and exploratory analysis to multivariate regression methods. Also discussed are the features and performance levels of statistical software packages that exist to apply the methods of analysis. Illustrative data sets are used throughout to describe methods of analysis and to report on results.

Statistics in Practice A new series of practical books outlining the use of statistical techniques in a wide range of application areas:
* Human and Biological Sciences
* Earth and Environmental Sciences
* Industry, Commerce and Finance
The authors of this important text explore the processes through which archaeologists analyse their data and how these can be made more rigorous and effective by sound statistical modelling. They assume relatively little previous statistical or mathematical knowledge. Introducing the idea underlying the Bayesian approach to the...

The investigation of the origin and formation of microstructures and the effect that microstructures has on the properties of materials are important issues in materials science and technology. Geometrical analysis is often the key to understanding the formation of microstructure and the resulting material properties.

This is the first book-length treatment of statistical surveillance methods used in financial analysis. It contains carefully selected chapters written by specialists from both fields and strikes a balance between the financial and statistical worlds, enhancing future collaborations between the two areas, and enabling more successful prediction of financial market trends. The book discusses, in detail, schemes for different control charts and different linear and nonlinear time series models and applies methods to real data from worldwide markets, as well as including simulation studies.

Large surveys are becoming increasingly available for public use, and researchers are often faced with the need to analyse complex survey data to address key scientific issues. For proper analysis it is also important to be aware of the different aspects of the design of complex surveys. Practical Methods for Design and Analysis of Complex Surveys features intermediate and advanced statistical techniques for use in designing and analysing complex surveys. This extensively updated edition features much new material, and detailed practical exercises with links to a Web site, helping instructors...

'Bayesian Belief Networks' presents: 1. An introduction to and definition of BBNs. 2. Step-by-step practical guidelines to applying BBNs. 3. A wide variety of applications in industry, natural sciences, services and computing. 4. A discussion of the future directions BBN research and applications might take.

Spatial point processes are mathematical models used to describe and analyse the geometrical structure of patterns formed by objects that are irregularly or randomly distributed in one-, two- or three-dimensional space. Examples include locations of trees in a forest, blood particles on a glass plate, galaxies in the universe, and particle centres in samples of material.

Numerous aspects of the nature of a specific spatial point pattern may be described using the appropriate statistical methods. Statistical Analysis and Modelling of Spatial Point Patterns provides a practical guide...

Statistical methodology plays a key role in ensuring that DNA evidence is collected, interpreted, analyzed, and presented correctly. With the recent advances in computer technology, this methodology is more complex than ever before. There are a growing number of books in the area but none are devoted to the computational analysis of evidence.

This book covers all the latest advances, as well as more established methods, in the application of statistical and optimisation methods within modern industry. These include applications from a range of industries that include micro-electronics, chemical, automotive, engineering, food, component assembly, household goods and plastics.