This study is based on the idea that Boltzmann-like modelling methods can be developed to design, with special attention to applied sciences, kinetic-type models which are called generalized kinetic models. In particular, these models appear in evolution equations for the statistical distribution ov
Recent Advances in Functional Data Analysis and Related Topics
β Scribed by A. Aguilera, M. C. Aguilera-Morillo (auth.), FrΓ©dΓ©ric Ferraty (eds.)
- Publisher
- Physica-Verlag Heidelberg
- Year
- 2011
- Tongue
- English
- Leaves
- 339
- Series
- Contributions to Statistics
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
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.
β¦ Table of Contents
Front Matter....Pages i-xviii
Penalized Spline Approaches for Functional Principal Component Logit Regression....Pages 1-7
Functional Prediction for the Residual Demand in Electricity Spot Markets....Pages 9-15
Variable Selection in Semi-Functional Regression Models....Pages 17-22
Power Analysis for Functional Change Point Detection....Pages 23-26
Robust Nonparametric Estimation for Functional Spatial Regression....Pages 27-31
Sequential Stability Procedures for Functional Data Setups....Pages 33-39
On the Effect of Noisy Observations of the Regressor in a Functional Linear Model....Pages 41-47
Testing the Equality of Covariance Operators....Pages 49-53
Modeling and Forecasting Monotone Curves by FDA....Pages 55-61
Wavelet-Based Minimum Contrast Estimation of Linear Gaussian Random Fields....Pages 63-69
Dimensionality Reduction for Samples of Bivariate Density Level Sets: an Application to Electoral Results....Pages 71-76
Structural Tests in Regression on Functional Variable....Pages 77-83
A Fast Functional Locally Modeled Conditional Density and Mode for Functional Time-Series....Pages 85-90
Generalized Additive Models for Functional Data....Pages 91-96
Recent Advances on Functional Additive Regression....Pages 97-102
Thresholding in Nonparametric Functional Regression with Scalar Response....Pages 103-109
Estimation of a Functional Single Index Model....Pages 111-116
Density Estimation for Spatial-Temporal Data....Pages 117-121
Functional Quantiles....Pages 123-129
Extremality for Functional Data....Pages 131-134
Functional Kernel Estimators of Conditional Extreme Quantiles....Pages 135-140
A Nonparametric Functional Method for Signature Recognition....Pages 141-147
Longitudinal Functional Principal Component Analysis....Pages 149-154
Estimation and Testing for Geostatistical Functional Data....Pages 155-160
Structured Penalties for Generalized Functional Linear Models (GFLM)....Pages 161-167
Consistency of the Mean and the Principal Components of Spatially Distributed Functional Data....Pages 169-175
Kernel Density Gradient Estimate....Pages 177-182
A Backward Generalization of PCA for Exploration and Feature Extraction of Manifold-Valued Shapes....Pages 183-187
Multiple Functional Regression with both Discrete and Continuous Covariates....Pages 189-195
Combining Factor Models and Variable Selection in High-Dimensional Regression....Pages 197-202
Factor Modeling for High Dimensional Time Series....Pages 203-207
Depth for Sparse Functional Data....Pages 209-212
Sparse Functional Linear Regression with Applications to Personalized Medicine....Pages 213-218
Estimation of Functional Coefficients in Partial Differential Equations....Pages 219-224
Functional Varying Coefficient Models....Pages 225-230
Applications of Funtional Data Analysis to Material Science....Pages 231-237
On the Properties of Functional Depth....Pages 239-244
Second-Order Inference for Functional Data with Application to DNA Minicircles....Pages 245-250
Nonparametric Functional Time Series Prediction....Pages 251-254
Wavelets Smoothing for Multidimensional Curves....Pages 255-261
Nonparametric Conditional Density Estimation for Functional Data. Econometric Applications....Pages 263-268
Spatial Functional Data Analysis....Pages 269-275
Clustering Spatially Correlated Functional Data....Pages 277-282
Spatial Clustering of Functional Data....Pages 283-289
Population-Wide Model-Free Quantification of Blood-Brain-Barrier Dynamics in Multiple Sclerosis....Pages 291-296
Flexible Modelling of Functional Data using Continuous Wavelet Dictionaries....Pages 297-300
Periodically Correlated Autoregressive Hilbertian Processes of Order p....Pages 301-306
Bases Giving Distances. A New Semimetric and its Use for Nonparametric Functional Data Analysis....Pages 307-313
Back Matter....Pages 315-320
β¦ Subjects
Statistics, general; Probability Theory and Stochastic Processes; Computer Imaging, Vision, Pattern Recognition and Graphics; Gene Expression; Meteorology/Climatology
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