Reciprocal Frame Architecture
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Reciprocal Frame Architecture
In structural terms reciprocal frame structures are 'three dimensional assemblies of mutually supporting beams'. But behind this definition lie some breathtakingly beautiful and complex structures at the heart of buildings both ancient and modern. This new book explores the principles of these apparently simple structures and demonstrates how they can be used in the context of a modern building. Starting with historic designs by de Honnecourt, Da Vinci and Serlio, the book presents the wealth of possible RF morphologies, and investigates the geometrical, structural and practical design issues of reciprocal frames. The case studies look at stunning examples of reciprocal frame architecture that range from low environmental impact buildings and self built examples in the UK and USA, to the fascinating and elegant structures of the Puppet Theatre in Seiwa, Tokyo's Spinning House, Sukiya –Yu house, The Toyoson Stonemason museum and the Life Sciences Laboratory – Torikabuto in Japan. The book is designed to inform and inspire architects and structural engineers alike, and brings to life a structural system whose principles have been used for thousands of years.
Reciprocal Frame Architecture
Simple and beautifully illustrated introduction to the use of reciprocal frame structures in architecture.
Exercises and Solutions in Statistical Theory
Exercises and Solutions in Statistical Theory helps students and scientists obtain an in-depth understanding of statistical theory by working on and reviewing solutions to interesting and challenging exercises of practical importance. Unlike similar books, this text incorporates many exercises that apply to real-world settings and provides much more thorough solutions. The exercises and selected detailed solutions cover from basic probability theory through to the theory of statistical inference. Many of the exercises deal with important, real-life scenarios in areas such as medicine, epidemiology, actuarial science, social science, engineering, physics, chemistry, biology, environmental health, and sports. Several exercises illustrate the utility of study design strategies, sampling from finite populations, maximum likelihood, asymptotic theory, latent class analysis, conditional inference, regression analysis, generalized linear models, Bayesian analysis, and other statistical topics. The book also contains references to published books and articles that offer more information about the statistical concepts. Designed as a supplement for advanced undergraduate and graduate courses, this text is a valuable source of classroom examples, homework problems, and examination questions. It is also useful for scientists interested in enhancing or refreshing their theoretical statistical skills. The book improves readers’ comprehension of the principles of statistical theory and helps them see how the principles can be used in practice. By mastering the theoretical statistical strategies necessary to solve the exercises, readers will be prepared to successfully study even higher-level statistical theory.