LEADER 06525nam 22007695 450 001 9910483540003321 005 20250610110236.0 010 $a3-030-47756-8 024 7 $a10.1007/978-3-030-47756-1 035 $a(CKB)5310000000016659 035 $a(MiAaPQ)EBC6232196 035 $a(DE-He213)978-3-030-47756-1 035 $a(PPN)24859592X 035 $a(MiAaPQ)EBC6231763 035 $a(MiAaPQ)EBC29092414 035 $a(EXLCZ)995310000000016659 100 $a20200619d2020 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aFunctional and High-Dimensional Statistics and Related Fields /$fedited by Germán Aneiros, Ivana Horová, Marie Hu?ková, Philippe Vieu 205 $a1st ed. 2020. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020. 215 $a1 online resource (270 pages) 225 1 $aContributions to Statistics,$x2628-8966 311 08$a3-030-47755-X 327 $aPreface -- List of Contributors -- 1 An introduction to the (postponed) 5th edition of the International Workshop on Functional and Operatorial Statistics -- 2 Analysis of Telecom Italia Mobile Phone Data by Space-time Regression with Differential Regularization -- 3 Some Numerical Test on the Convergence Rates of Regression with Differential Regularization -- 4 Learning with Signatures -- 5 About the Complexity Function in Small-ball Probability Factorization -- 6 Principal Components Analysis of a Cyclostationary Random Function -- 7 Level Set and Density Estimation on Manifolds -- 8 Pseudo-metrics as Interesting Tool in Nonparametric Functional Regression -- 9 Testing a Specification Form in Single Functional Index Model -- 10 A New Method for Ordering Functional Data and its Application to Diagnostic Test -- 11 A Functional Data Analysis Approach to the Estimation of Densities over Complex Regions -- 12 A Conformal Approach for Distribution-free Prediction of Functional Data -- 13 G-Lasso Network Analysis for Functional Data -- 14 Modelling Functional Data with High-dimensional Error Structure -- 15 Goodness-of-fit Tests for Functional Linear Models Based on Integrated Projections -- 16 From High-dimensional to Functional Data: Stringing Via Manifold Learning -- 17 Functional Two-sample Tests Based on Empirical Characteristic Functionals -- 18 Some Remarks on the Nelson?Siegel Model -- 19 Modeling the Effect of Recurrent Events on Time-to-event Processes by Means of Functional Data -- 20 On Robust Training of Regression Neural Networks -- 21 Simultaneous Inference for Function-valued Parameters: a Fast and Fair Approach -- 22 Single Functional Index Model under Responses MAR and Dependent Observations -- 23 O2S2 for the Geodata Deluge -- 24 Riemannian Distances between Covariance Operators and Gaussian Processes -- 25 Depth in Infinite-dimensional Spaces -- 26 Variable Selection in Semiparametric Bi-functional Models -- 27 Local Inference for Functional Data Controlling the Functional False Discovery Rate -- 28 Optimum Scale Selection for 3D Point Cloud Classification through Distance Correlation -- 29 Generalized Functional Partially Linear Single-index Models -- 30 Functional Outlier Detection through Probabilistic Modelling -- 31 Topological Object Data Analysis Methods with an Application to Medical Imaging -- 32 Distribution-free Pointwise Adjusted %-values for Functional Hypotheses -- Authors Index. 330 $aThis book presents the latest research on the statistical analysis of functional, high-dimensional and other complex data, addressing methodological and computational aspects, as well as real-world applications. It covers topics like classification, confidence bands, density estimation, depth, diagnostic tests, dimension reduction, estimation on manifolds, high- and infinite-dimensional statistics, inference on functional data, networks, operatorial statistics, prediction, regression, robustness, sequential learning, small-ball probability, smoothing, spatial data, testing, and topological object data analysis, and includes applications in automobile engineering, criminology, drawing recognition, economics, environmetrics, medicine, mobile phone data, spectrometrics and urban environments. The book gathers selected, refereed contributions presented at the Fifth International Workshop on Functional and Operatorial Statistics (IWFOS) in Brno, Czech Republic. The workshop was originally to be held on June 24-26, 2020, but had to be postponed as a consequence of the COVID-19 pandemic. Initiated by the Working Group on Functional and Operatorial Statistics at the University of Toulouse in 2008, the IWFOS workshops provide a forum to discuss the latest trends and advances in functional statistics and related fields, and foster the exchange of ideas and international collaboration in the field. 410 0$aContributions to Statistics,$x2628-8966 606 $aStatistics 606 $aMathematical statistics$xData processing 606 $aStatistics 606 $aBiometry 606 $aBig data 606 $aQuantitative research 606 $aStatistical Theory and Methods 606 $aStatistics and Computing 606 $aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences 606 $aBiostatistics 606 $aBig Data 606 $aData Analysis and Big Data 615 0$aStatistics. 615 0$aMathematical statistics$xData processing. 615 0$aStatistics. 615 0$aBiometry. 615 0$aBig data. 615 0$aQuantitative research. 615 14$aStatistical Theory and Methods. 615 24$aStatistics and Computing. 615 24$aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences. 615 24$aBiostatistics. 615 24$aBig Data. 615 24$aData Analysis and Big Data. 676 $a519.5 702 $aAneiros$b Germán$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aHorová$b Ivana$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aHu?ková$b Marie$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aVieu$b Philippe$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910483540003321 996 $aFunctional and High-Dimensional Statistics and Related Fields$92369194 997 $aUNINA