Martin Fowler is a consultant specializing in object-oriented analysis and design. This book presents and discusses a number of object models derived from various problem domains. All patterns and models presented have been derived from the author's own consulting work and are based on real business cases.

This innovative book recognizes the need within the object-oriented community for a book that goes beyond the tools and techniques of the typical methodology book. In Analysis Patterns: Reusable Object Models, Martin Fowler focuses on the end result of object-oriented analysis and design—the models themselves. He shares with you his wealth of object modeling experience and his keen eye for identifying repeating problems and transforming them into reusable models. Analysis Patterns provides a catalogue of patterns that have emerged in a wide range of domains including trading, measurement, accounting and organizational relationships. Recognizing that conceptual patterns cannot exist in isolation, the author also presents a series of "support patterns" that discuss how to turn conceptual models into software that in turn fits into an architecture for a large information system. Included in each pattern is the reasoning behind their design, rules for when they should and should not be used, and tips for implementation. The examples presented in this book comprise a cookbook of useful models and insight into the skill of reuse that will improve analysis, modeling and implementation.

- Exploit the significant power of design patterns and make better design decisions with the proven POAD methodology - Improve software quality and reliability while reducing costs and maintenance efforts - Practical case studies and illustrative examples help the reader manage the complexity of software development

Martin Pring is one of the most respected and well-known experts on technical analysis. People such as John Murphy and John Bollinger speak well of him, and Mr. Pring is certianly one of teh most sought after speakers for investing and trading conferences around the country. Martin Pring now focuses on price patterns, one of the hottest subjects among traders today. Martin Pring on Price Patterns provides a complete, in-depth explanation of all widely used price patterns. He begins by outlining the basic building blocks used in techncial analysis and shows how they apply to price patterns analysis.

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 to the use of these specialised methods. The application-oriented approach helps demonstrate the benefits of this increasingly popular branch of statistics to a broad audience. The book: Provides an introduction to spatial point patterns for researchers across numerous areas of application Adopts an extremely accessible style, allowing the non-statistician complete understanding Describes the process of extracting knowledge from the data, emphasising the marked point process Demonstrates the analysis of complex datasets, using applied examples from areas including biology, forestry, and materials science Features a supplementary website containing example datasets. Statistical Analysis and Modelling of Spatial Point Patterns is ideally suited for researchers in the many areas of application, including environmental statistics, ecology, physics, materials science, geostatistics, and biology. It is also suitable for students of statistics, mathematics, computer science, biology and geoinformatics.

Software analysis patterns play an important role in reducing the overall cost and compressing the time of software project lifecycles. However, building reusable and stable software analysis patterns is still considered a major and delicate challenge. This book proposes a novel concept for building analysis patterns based on software stability and is a modern approach for building stable, highly reusable, and widely applicable analysis patterns. The book also aims to promote better understanding of problem spaces and discusses how to focus requirements analysis accurately. It demonstrates a new approach to discovering and creating stable analysis patterns (SAPs). This book presents a pragmatic approach to understanding problem domains, utilizing SAPs for any field of knowledge, and modeling stable software systems, components, and frameworks. It helps readers attain the basic knowledge that is needed to analyze and extract analysis patterns from any domain of interest. Readers also learn to master methods to document patterns in an effective, easy, and comprehensible manner. Bringing significant contributions to the field of computing, this book is a unique and comprehensive reference manual on SAPs. It provides insight on handling the understanding of problem spaces and supplies methods and processes to analyze user requirements accurately as well as ways to use SAPs in building myriad cost-effective and highly maintainable systems. The book also shows how to link SAPs to the design phase thereby ensuring a smooth transition between analysis and design.

This is a new edition of the classic monograph, published in 1983, that described those statistical methods that are used to analyse spatial data. This edition has been entirely updated with the latest developments in the analysis of spatial data which have grown to become a large area of concern in environmental and epidemiological research. There is a website connected with the volume that contains additional data sets and a new chapter on spatial epidemiology. It is appropriate for graduate level statisticians in various disciplines.