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"As technology progresses, we are able to handle larger and larger datasets. At the same time, monitoring devices such as electronic equipment and sensors (for registering images, temperature, etc.) have become more and more sophisticated. This high-tech revolution offers the opportunity to observe phenomena in an increasingly accurate way by producing statistical units sampled over a finer and finer grid, with the measurement points so close that the data can be considered as observations varying over a continuum. Such continuous (or functional) data may occur in biomechanics (e.g. human movements), chemometrics (e.g. spectrometric curves), econometrics (e.g. the stock market index), geophysics (e.g. spatio-temporal events such as El Nino or time series of satellite images), or medicine (electro-cardiograms/electro-encephalograms). It is well known that standard multivariate statistical analyses fail with functional data. However, the great potential for applications has encouraged new methodologies able to extract relevant information from functional datasets. This Handbook aims to present a state of the art exploration of this high-tech field, by gathering together most of major advances in this area. Leading international experts have contributed to this volume with each chapter giving the key original ideas and comprehensive bibliographical information. The main statistical topics (classification, inference, factor-based analysis, regression modelling, resampling methods, time series, random processes) are covered in the setting of functional data. The twin challenges of the subject are the practical issues of implementing new methodologies and the theoretical techniques needed to expand the mathematical foundations and toolbox. The volume therefore mixes practical, methodological and theoretical aspects of the subject, sometimes within the same chapter. As a consequence, this book should appeal to a wide audience of engineers, practitioners and graduate students, as well as academic researchers, not only in statistics and probability but also in the numerous related application areas"

Multivariate analysis --- Statistical functionals

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Asymptotic distribution (Probability theory) --- Estimation theory --- Statistical functionals --- Distribution asymptotique (Théorie des probabilités) --- Théorie de l'estimation

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New technologies allow us to handle increasingly large datasets, while monitoring devices are becoming ever more sophisticated. This high-tech progress produces statistical units sampled over finer and finer grids. As the measurement points become closer, the data can be considered as observations varying over a continuum. This intrinsic continuous data (called functional data) can be found in various fields of science, including biomechanics, chemometrics, econometrics, environmetrics, geophysics, medicine, etc. The failure of standard multivariate statistics to analyze such functional data has led the statistical community to develop appropriate statistical methodologies, called Functional Data Analysis (FDA). Today, FDA is certainly one of the most motivating and popular statistical topics due to its impact on crucial societal issues (health, environment, etc). This is why the FDA statistical community is rapidly growing, as are the statistical developments . Therefore, it is necessary to organize regular meetings in order to provide a state-of-art review of the recent advances in this fascinating area. This book collects selected and extended papers presented at  the second International Workshop of Functional and Operatorial Statistics (Santander, Spain, 16-18 June, 2011), in which many outstanding experts on FDA will present the most relevant advances in this pioneering statistical area. Undoubtedly, these proceedings will be an essential resource for academic researchers, master students, engineers, and practitioners not only in statistics but also in numerous related fields of application.  .

Characteristic functions. --- Multivariate analysis. --- Probabilities. --- Statistical functionals. --- Multivariate analysis --- Statistical functionals --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Multivariate distributions --- Multivariate statistical analysis --- Statistical analysis, Multivariate --- Statistics. --- Gene expression. --- Atmospheric sciences. --- Computer graphics. --- Statistics, general. --- Probability Theory and Stochastic Processes. --- Computer Imaging, Vision, Pattern Recognition and Graphics. --- Gene Expression. --- Atmospheric Sciences. --- Analysis of variance --- Mathematical statistics --- Matrices --- Functionals --- Distribution (Probability theory. --- Computer vision. --- Machine vision --- Vision, Computer --- Artificial intelligence --- Image processing --- Pattern recognition systems --- Distribution functions --- Frequency distribution --- Characteristic functions --- Probabilities --- Genes --- Genetic regulation --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Econometrics --- Expression --- Statistics . --- Optical data processing. --- Atmospheric sciences --- Earth sciences --- Atmosphere --- Optical computing --- Visual data processing --- Bionics --- Electronic data processing --- Integrated optics --- Photonics --- Computers --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Risk --- Optical equipment --- Molecular genetics. --- Atmospheric science. --- Probability Theory. --- Molecular Genetics. --- Atmospheric Science. --- Digital techniques. --- Digital image processing --- Digital electronics --- Genetics --- Molecular biology