Recent Advances in Functional Data Analysis and Related Topics

Front Cover
Frédéric Ferraty
Springer Science & Business Media, Jun 15, 2011 - Mathematics - 322 pages

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.

 

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Contents

Penalized Spline Approaches for Functional Principal Component Logit Regression
1
Functional Prediction for the Residual Demand in Electricity Spot Markets
9
Variable Selection in SemiFunctional Regression Models
17
Power Analysis for Functional Change Point Detection
23
Robust Nonparametric Estimation for Functional Spatial Regression
27
Sequential Stability Procedures for Functional Data Setups
33
On the Effect of Noisy Observations of the Regressor in a Functional Linear Model
41
Testing the Equality of Covariance Operators
49
Consistency of the Mean and the Principal Components of Spatially Distributed Functional Data
169
Kernel Density Gradient Estimate
177
A Backward Generalization of PCA for Exploration and Feature Extraction of ManifoldValued Shapes
183
Multiple Functional Regression with both Discrete and Continuous Covariates
189
Combining Factor Models and Variable Selection in HighDimensional Regression
197
Factor Modeling for High Dimensional Time Series
203
Depth for Sparse Functional Data
209
Sparse Functional Linear Regression with Applications to Personalized Medicine
213

Modeling and Forecasting Monotone Curves by FDA
55
WaveletBased Minimum Contrast Estimation of Linear Gaussian Random Fields
63
Dimensionality Reduction for Samples of Bivariate Density Level Sets an Application to Electoral Results
71
Structural Tests in Regression on Functional Variable
77
A Fast Functional Locally Modeled Conditional Density and Mode for Functional TimeSeries
85
Generalized Additive Models for Functional Data
91
Recent Advances on Functional Additive Regression
97
Thresholding in Nonparametric Functional Regression with Scalar Response
103
Estimation of a Functional Single Index Model
111
Density Estimation for SpatialTemporal Data
117
Functional Quantiles
123
Extremality for Functional Data
131
Functional Kernel Estimators of Conditional Extreme Quantiles
135
A Nonparametric Functional Method for Signature Recognition
141
Longitudinal Functional Principal Component Analysis
149
Estimation and Testing for Geostatistical Functional Data
155
Structured Penalties for Generalized Functional Linear Models GFLM
161
Estimation of Functional Coefficients in Partial Differential Equations
219
Functional Varying Coefficient Models
225
Applications of Funtional Data Analysis to Material Science
231
On the Properties of Functional Depth
239
SecondOrder Inference for Functional Data with Application to DNA Minicircles
245
Nonparametric Functional Time Series Prediction
251
Wavelets Smoothing for Multidimensional Curves
255
Nonparametric Conditional Density Estimation for Functional Data Econometric Applications
263
Spatial Functional Data Analysis
269
Clustering Spatially Correlated Functional Data
277
Spatial Clustering of Functional Data
283
PopulationWide ModelFree Quantification of BloodBrainBarrier Dynamics in Multiple Sclerosis
291
Flexible Modelling of Functional Data using Continuous Wavelet Dictionaries
297
Periodically Correlated Autoregressive Hilbertian Processes of Order p
301
Bases Giving Distances A New Semimetric and its Use for Nonparametric Functional Data Analysis
307
List of Contributors
315
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