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Originally published in 1938. Many of the earliest books, particularly those dating back to the 1900s and before, are now extremely scarce and increasingly expensive. Obscure Press are republishing these classic works in affordable, high quality, modern editions, using the original text and artwork.
Included here are expressions in the functional domain of such classics as linear regression, principal components analysis, linear modelling, and canonical correlation analysis, as well as specifically functional techniques such as curve registration and principal differential analysis. Data arising in real applications are used throughout for both motivation and illustration, showing how functional approaches allow us to see new things, especially by exploiting the smoothness of the processes generating the data. The data sets exemplify the wide scope of functional data analysis; they are drawn from growth analysis, meteorology, biomechanics, equine science, economics, and medicine. The book presents novel statistical technology while keeping the mathematical level widely accessible. It is designed to appeal to students, applied data analysts, and to experienced researchers; and as such is of value both within statistics and across a broad spectrum of other fields. Much of the material appears here for the first time.
The book provides an application-oriented overview of functional analysis, with extended and accessible presentations of key concepts such as spline basis functions, data smoothing, curve registration, functional linear models and dynamic systems Functional data analysis is put to work in a wide a range of applications, so that new problems are likely to find close analogues in this book The code in R and Matlab in the book has been designed to permit easy modification to adapt to new data structures and research problems
The first part of this book deals with Britain’s imperial age, its militants and its critics. The selection of works generates a large field of debate explored using traditional or innovative approaches. The 19th century is presented as a time for writers (J. E. Aylmer, E. Marryat Norris, G. A. Henty, Conan Doyle) who tell stories of Europeans venturing forth into “uncivilised” regions of the world where they meet other races. But writers of a different outlook are also considered. Before the twilight of Empire, women were born in England (Virginia Woolf) and in Ireland (Elizabeth Bowen) who would use the ductile means of literature to narrate journeys into the female self, instead of ...
This text focuses on the use of smoothing methods for developing and estimating differential equations following recent developments in functional data analysis and building on techniques described in Ramsay and Silverman (2005) Functional Data Analysis. The central concept of a dynamical system as a buffer that translates sudden changes in input into smooth controlled output responses has led to applications of previously analyzed data, opening up entirely new opportunities for dynamical systems. The technical level has been kept low so that those with little or no exposure to differential equations as modeling objects can be brought into this data analysis landscape. There are already many texts on the mathematical properties of ordinary differential equations, or dynamic models, and there is a large literature distributed over many fields on models for real world processes consisting of differential equations. However, a researcher interested in fitting such a model to data, or a statistician interested in the properties of differential equations estimated from data will find rather less to work with. This book fills that gap.
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