Recent advances in functional data analysis and related topics
Author(s)
Bibliographic Information
Recent advances in functional data analysis and related topics
(Contributions to statistics)
Physica-Verlag, c2011
Available at 4 libraries
  Aomori
  Iwate
  Miyagi
  Akita
  Yamagata
  Fukushima
  Ibaraki
  Tochigi
  Gunma
  Saitama
  Chiba
  Tokyo
  Kanagawa
  Niigata
  Toyama
  Ishikawa
  Fukui
  Yamanashi
  Nagano
  Gifu
  Shizuoka
  Aichi
  Mie
  Shiga
  Kyoto
  Osaka
  Hyogo
  Nara
  Wakayama
  Tottori
  Shimane
  Okayama
  Hiroshima
  Yamaguchi
  Tokushima
  Kagawa
  Ehime
  Kochi
  Fukuoka
  Saga
  Nagasaki
  Kumamoto
  Oita
  Miyazaki
  Kagoshima
  Okinawa
  Korea
  China
  Thailand
  United Kingdom
  Germany
  Switzerland
  France
  Belgium
  Netherlands
  Sweden
  Norway
  United States of America
Note
Includes bibliographical references
Description and Table of Contents
Description
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.
Table of Contents
Penalized Spline Approaches for Functional Principal Component Logit.- Functional Prediction for the Residual Demand in Electricity Spot .- Variable Selection in Semi-Functional RegressionModels.- Power Analysis for Functional Change Point Detection.- Robust Nonparametric Estimation for Functional Spatial Regression.- Sequential Stability Procedures for Functional Data Setups.- On the Effect of Noisy Observations of the Regressor in a Functional Linear Model.- Testing the Equality of Covariance Operators.- Modeling and Forecasting Monotone Curves by FDA.- Wavelet-Based Minimum Contrast Estimation of Linear Gaussian Random Fields.- Dimensionality Reduction for Samples of Bivariate Density Level Sets: an Application to Electoral Results.- Structural Tests in Regression on Functional Variable.- A Fast Functional Locally Modeled Conditional Density and Mode for Functional Time-Series.- Generalized Additive Models for Functional Data.- Recent Advances on Functional Additive Regression.- Thresholding in Nonparametric Functional Regression with Scalar Response.- Estimation of a Functional Single Index Model.- Density Estimation for Spatial-Temporal Data.- Functional Quantiles.- Extremality for Functional Data.- Functional Kernel Estimators of Conditional Extreme Quantiles.- A Nonparametric Functional Method for Signature Recognition.- Longitudinal Functional Principal Component Analysis.- Estimation and Testing for Geostatistical Functional Data.- Structured Penalties for Generalized Functional Linear Models (GFLM).- Consistency of the Mean and the Principal Components of Spatially Distributed Functional Data.- Kernel Density Gradient Estimate.- A Backward Generalization of PCA for Exploration and Feature Extraction of Manifold-Valued Shapes.- Multiple Functional Regression with both Discrete and Continuous Covariates.- Factor Modeling for High Dimensional Time Series.- Depth for Sparse Functional Data.- Sparse Functional Linear Regression with Applications to Personalized Medicine.- Estimation of Functional Coefficients in Partial Differential Equations.- Functional Varying Coefficient Models.- Applications of Functional Data Analysis to Material Science.- On the Properties of Functional Dept.- Second-Order Inference for Functional Data with Application to DNA Minicircles.- Nonparametric Functional Time Series Prediction.- Wavelets Smoothing for Multidimensional Curves.- Nonparametric Conditional Density Estimation for Functional Data. Econometric Applications.
by "Nielsen BookData"