Most chapters include exercises so the text could easily be used as a text in a course on FDA. I strongly recommend the book and will briefly describe each chapter. … The goal is to educate and equip the reader for research in and/or implementation of FDA. “The intended audience is anybody performing FDA who must implement or use FDA software. students as well as other scientists with a reasonably deep quantitative background.” (Jeffrey S. … it would be a good basis for an applied course in functional data analysis that could be taken by statistics and biostatistics M.S. I recommend this book for statisticians wanting to learn about the basics of functional data analysis, as well as practitioners wanting to explore their own data and perform some analyses on their own. “This well-written book provides a great, intuitive introduction to functional data analysis …. It therefore provides an excellent starting point for those who would like to make use of these very powerful techniques in analyzing data.” (Journal of Statistical Software, April 2010, Vol.
#Matlab 2009 code#
The mixture of R and RATLAB illustrative code works well and the latter computing environment, together with the material on dynamics, will suit those from an engineering or physical sciences background. It gives a brief but clear description of the concepts and methods together with a strong focus on implementation. “The book is intended as a means of introducing functional data analysis to those who would like to use it as a research tool in a variety of applications. He has made substantive contributions to several CRAN packages including ‘fda’ and ‘DierckxSpline.’ Keywords Spencer Graves is an engineer with a PhD in Statistics and over 15 years experience using S-Plus and R to analyze data in a broad range of applications. His research interests include statistical inference in nonlinear dynamics, machine learning and computational statistics. Giles Hooker is Assistant Professor of Biological Statistics and Computational Biology at Cornell University. His statistical work draws on his collaboration with researchers in biomechanics, chemical engineering, climatology, ecology, economics, human biology, medicine and psychology. He was President of the Statistical Society of Canada in 2002-3 and holds the Society’s Gold Medal for his work in functional data analysis. Jim Ramsay is Professor Emeritus at McGill University and is an international authority on many aspects of multivariate analysis. The companion 'fda' package for R includes script files to reproduce nearly all the examples in the book including all but one of the 76 figures. This book is accompanied by additional web-based support at for applying existing functions and developing new ones in either language. The authors make it easy to get up and running in new applications by adapting the code for the examples, and by being able to access the details of key functions within these pages. It complements Functional Data Analysis, Second Edition and Applied Functional Data Analysis: Methods and Case Studies by providing computer code in both the R and Matlab languages for a set of data analyses that showcase functional data analysis techniques.
#Matlab 2009 series#
This volume in the UseR! Series is aimed at a wide range of readers, and especially those who would like apply these techniques to their research problems. Scientists often collect samples of curves and other functional observations, and develop models where parameters are also functions.
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