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Inference and prediction in large dimensions [[electronic resource] /] / Denis Bosq, Delphine Blanke
| Inference and prediction in large dimensions [[electronic resource] /] / Denis Bosq, Delphine Blanke |
| Autore | Bosq Denis <1939-> |
| Pubbl/distr/stampa | Chichester, England ; ; Hoboken, NJ, : John Wiley/Dunod, c2007 |
| Descrizione fisica | 1 online resource (338 p.) |
| Disciplina |
519.5/44
519.54 |
| Altri autori (Persone) | BlankeDelphine |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Estimation theory
Nonparametric statistics Stochastic processes Prediction theory |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-282-12309-2
9786612123092 0-470-72403-X 0-470-72402-1 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Inference and Prediction in Large Dimensions; Contents; List of abbreviations; Introduction; Part I Statistical Prediction Theory; 1 Statistical prediction; 1.1 Filtering; 1.2 Some examples; 1.3 The prediction model; 1.4 P-sufficient statistics; 1.5 Optimal predictors; 1.6 Efficient predictors; 1.7 Loss functions and empirical predictors; 1.7.1 Loss function; 1.7.2 Location parameters; 1.7.3 Bayesian predictors; 1.7.4 Linear predictors; 1.8 Multidimensional prediction; Notes; 2 Asymptotic prediction; 2.1 Introduction; 2.2 The basic problem; 2.3 Parametric prediction for stochastic processes
2.4 Predicting some common processes2.5 Equivalent risks; 2.6 Prediction for small time lags; 2.7 Prediction for large time lags; Notes; Part II Inference by Projection; 3 Estimation by adaptive projection; 3.1 Introduction; 3.2 A class of functional parameters; 3.3 Oracle; 3.4 Parametric rate; 3.5 Nonparametric rates; 3.6 Rate in uniform norm; 3.7 Adaptive projection; 3.7.1 Behaviour of truncation index; 3.7.2 Superoptimal rate; 3.7.3 The general case; 3.7.4 Discussion and implementation; 3.8 Adaptive estimation in continuous time; Notes; 4 Functional tests of fit 4.1 Generalized chi-square tests4.2 Tests based on linear estimators; 4.2.1 Consistency of the test; 4.2.2 Application; 4.3 Efficiency of functional tests of fit; 4.3.1 Adjacent hypotheses; 4.3.2 Bahadur efficiency; 4.4 Tests based on the uniform norm; 4.5 Extensions. Testing regression; 4.6 Functional tests for stochastic processes; Notes; 5 Prediction by projection; 5.1 A class of nonparametric predictors; 5.2 Guilbart spaces; 5.3 Predicting the conditional distribution; 5.4 Predicting the conditional distribution function; Notes; Part III Inference by Kernels 6 Kernel method in discrete time6.1 Presentation of the method; 6.2 Kernel estimation in the i.i.d. case; 6.3 Density estimation in the dependent case; 6.3.1 Mean-square error and asymptotic normality; 6.3.2 Almost sure convergence; 6.4 Regression estimation in the dependent case; 6.4.1 Framework and notations; 6.4.2 Pointwise convergence; 6.4.3 Uniform convergence; 6.5 Nonparametric prediction by kernel; 6.5.1 Prediction for a stationary Markov process of order k; 6.5.2 Prediction for general processes; Notes; 7 Kernelmethodin continuous time 7.1 Optimal and superoptimal rates for density estimation7.1.1 The optimal framework; 7.1.2 The superoptimal case; 7.2 From optimal to superoptimal rates; 7.2.1 Intermediate rates; 7.2.2 Classes of processes and examples; 7.2.3 Mean-square convergence; 7.2.4 Almost sure convergence; 7.2.5 An adaptive approach; 7.3 Regression estimation; 7.3.1 Pointwise almost sure convergence; 7.3.2 Uniform almost sure convergence; 7.4 Nonparametric prediction by kernel; Notes; 8 Kernel method from sampled data; 8.1 Density estimation; 8.1.1 High rate sampling; 8.1.2 Adequate sampling schemes 8.2 Regression estimation |
| Record Nr. | UNINA-9910144718003321 |
Bosq Denis <1939->
|
||
| Chichester, England ; ; Hoboken, NJ, : John Wiley/Dunod, c2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Inference and prediction in large dimensions [[electronic resource] /] / Denis Bosq, Delphine Blanke
| Inference and prediction in large dimensions [[electronic resource] /] / Denis Bosq, Delphine Blanke |
| Autore | Bosq Denis <1939-> |
| Pubbl/distr/stampa | Chichester, England ; ; Hoboken, NJ, : John Wiley/Dunod, c2007 |
| Descrizione fisica | 1 online resource (338 p.) |
| Disciplina |
519.5/44
519.54 |
| Altri autori (Persone) | BlankeDelphine |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Estimation theory
Nonparametric statistics Stochastic processes Prediction theory |
| ISBN |
1-282-12309-2
9786612123092 0-470-72403-X 0-470-72402-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Inference and Prediction in Large Dimensions; Contents; List of abbreviations; Introduction; Part I Statistical Prediction Theory; 1 Statistical prediction; 1.1 Filtering; 1.2 Some examples; 1.3 The prediction model; 1.4 P-sufficient statistics; 1.5 Optimal predictors; 1.6 Efficient predictors; 1.7 Loss functions and empirical predictors; 1.7.1 Loss function; 1.7.2 Location parameters; 1.7.3 Bayesian predictors; 1.7.4 Linear predictors; 1.8 Multidimensional prediction; Notes; 2 Asymptotic prediction; 2.1 Introduction; 2.2 The basic problem; 2.3 Parametric prediction for stochastic processes
2.4 Predicting some common processes2.5 Equivalent risks; 2.6 Prediction for small time lags; 2.7 Prediction for large time lags; Notes; Part II Inference by Projection; 3 Estimation by adaptive projection; 3.1 Introduction; 3.2 A class of functional parameters; 3.3 Oracle; 3.4 Parametric rate; 3.5 Nonparametric rates; 3.6 Rate in uniform norm; 3.7 Adaptive projection; 3.7.1 Behaviour of truncation index; 3.7.2 Superoptimal rate; 3.7.3 The general case; 3.7.4 Discussion and implementation; 3.8 Adaptive estimation in continuous time; Notes; 4 Functional tests of fit 4.1 Generalized chi-square tests4.2 Tests based on linear estimators; 4.2.1 Consistency of the test; 4.2.2 Application; 4.3 Efficiency of functional tests of fit; 4.3.1 Adjacent hypotheses; 4.3.2 Bahadur efficiency; 4.4 Tests based on the uniform norm; 4.5 Extensions. Testing regression; 4.6 Functional tests for stochastic processes; Notes; 5 Prediction by projection; 5.1 A class of nonparametric predictors; 5.2 Guilbart spaces; 5.3 Predicting the conditional distribution; 5.4 Predicting the conditional distribution function; Notes; Part III Inference by Kernels 6 Kernel method in discrete time6.1 Presentation of the method; 6.2 Kernel estimation in the i.i.d. case; 6.3 Density estimation in the dependent case; 6.3.1 Mean-square error and asymptotic normality; 6.3.2 Almost sure convergence; 6.4 Regression estimation in the dependent case; 6.4.1 Framework and notations; 6.4.2 Pointwise convergence; 6.4.3 Uniform convergence; 6.5 Nonparametric prediction by kernel; 6.5.1 Prediction for a stationary Markov process of order k; 6.5.2 Prediction for general processes; Notes; 7 Kernelmethodin continuous time 7.1 Optimal and superoptimal rates for density estimation7.1.1 The optimal framework; 7.1.2 The superoptimal case; 7.2 From optimal to superoptimal rates; 7.2.1 Intermediate rates; 7.2.2 Classes of processes and examples; 7.2.3 Mean-square convergence; 7.2.4 Almost sure convergence; 7.2.5 An adaptive approach; 7.3 Regression estimation; 7.3.1 Pointwise almost sure convergence; 7.3.2 Uniform almost sure convergence; 7.4 Nonparametric prediction by kernel; Notes; 8 Kernel method from sampled data; 8.1 Density estimation; 8.1.1 High rate sampling; 8.1.2 Adequate sampling schemes 8.2 Regression estimation |
| Record Nr. | UNINA-9910830304003321 |
|
Bosq Denis <1939->
|
||
| Chichester, England ; ; Hoboken, NJ, : John Wiley/Dunod, c2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Inference and prediction in large dimensions / / Denis Bosq, Delphine Blanke
| Inference and prediction in large dimensions / / Denis Bosq, Delphine Blanke |
| Autore | Bosq Denis <1939-> |
| Pubbl/distr/stampa | Chichester, England ; ; Hoboken, NJ, : John Wiley/Dunod, c2007 |
| Descrizione fisica | 1 online resource (338 p.) |
| Disciplina | 519.5/44 |
| Altri autori (Persone) | BlankeDelphine |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Estimation theory
Nonparametric statistics Stochastic processes Prediction theory |
| ISBN |
1-282-12309-2
9786612123092 0-470-72403-X 0-470-72402-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Inference and Prediction in Large Dimensions; Contents; List of abbreviations; Introduction; Part I Statistical Prediction Theory; 1 Statistical prediction; 1.1 Filtering; 1.2 Some examples; 1.3 The prediction model; 1.4 P-sufficient statistics; 1.5 Optimal predictors; 1.6 Efficient predictors; 1.7 Loss functions and empirical predictors; 1.7.1 Loss function; 1.7.2 Location parameters; 1.7.3 Bayesian predictors; 1.7.4 Linear predictors; 1.8 Multidimensional prediction; Notes; 2 Asymptotic prediction; 2.1 Introduction; 2.2 The basic problem; 2.3 Parametric prediction for stochastic processes
2.4 Predicting some common processes2.5 Equivalent risks; 2.6 Prediction for small time lags; 2.7 Prediction for large time lags; Notes; Part II Inference by Projection; 3 Estimation by adaptive projection; 3.1 Introduction; 3.2 A class of functional parameters; 3.3 Oracle; 3.4 Parametric rate; 3.5 Nonparametric rates; 3.6 Rate in uniform norm; 3.7 Adaptive projection; 3.7.1 Behaviour of truncation index; 3.7.2 Superoptimal rate; 3.7.3 The general case; 3.7.4 Discussion and implementation; 3.8 Adaptive estimation in continuous time; Notes; 4 Functional tests of fit 4.1 Generalized chi-square tests4.2 Tests based on linear estimators; 4.2.1 Consistency of the test; 4.2.2 Application; 4.3 Efficiency of functional tests of fit; 4.3.1 Adjacent hypotheses; 4.3.2 Bahadur efficiency; 4.4 Tests based on the uniform norm; 4.5 Extensions. Testing regression; 4.6 Functional tests for stochastic processes; Notes; 5 Prediction by projection; 5.1 A class of nonparametric predictors; 5.2 Guilbart spaces; 5.3 Predicting the conditional distribution; 5.4 Predicting the conditional distribution function; Notes; Part III Inference by Kernels 6 Kernel method in discrete time6.1 Presentation of the method; 6.2 Kernel estimation in the i.i.d. case; 6.3 Density estimation in the dependent case; 6.3.1 Mean-square error and asymptotic normality; 6.3.2 Almost sure convergence; 6.4 Regression estimation in the dependent case; 6.4.1 Framework and notations; 6.4.2 Pointwise convergence; 6.4.3 Uniform convergence; 6.5 Nonparametric prediction by kernel; 6.5.1 Prediction for a stationary Markov process of order k; 6.5.2 Prediction for general processes; Notes; 7 Kernelmethodin continuous time 7.1 Optimal and superoptimal rates for density estimation7.1.1 The optimal framework; 7.1.2 The superoptimal case; 7.2 From optimal to superoptimal rates; 7.2.1 Intermediate rates; 7.2.2 Classes of processes and examples; 7.2.3 Mean-square convergence; 7.2.4 Almost sure convergence; 7.2.5 An adaptive approach; 7.3 Regression estimation; 7.3.1 Pointwise almost sure convergence; 7.3.2 Uniform almost sure convergence; 7.4 Nonparametric prediction by kernel; Notes; 8 Kernel method from sampled data; 8.1 Density estimation; 8.1.1 High rate sampling; 8.1.2 Adequate sampling schemes 8.2 Regression estimation |
| Record Nr. | UNINA-9910877234203321 |
|
Bosq Denis <1939->
|
||
| Chichester, England ; ; Hoboken, NJ, : John Wiley/Dunod, c2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Nonparametric Statistics : 3rd ISNPS, Avignon, France, June 2016 / / edited by Patrice Bertail, Delphine Blanke, Pierre-André Cornillon, Eric Matzner-Løber
| Nonparametric Statistics : 3rd ISNPS, Avignon, France, June 2016 / / edited by Patrice Bertail, Delphine Blanke, Pierre-André Cornillon, Eric Matzner-Løber |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (388 pages) |
| Disciplina | 519.54 |
| Collana | Springer Proceedings in Mathematics & Statistics |
| Soggetto topico |
Statistics
Statistical Theory and Methods Statistics and Computing/Statistics Programs Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Statistics for Business, Management, Economics, Finance, Insurance Statistics for Life Sciences, Medicine, Health Sciences |
| ISBN | 3-319-96941-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Symmetrizing k-nn and Mutual k-nn Smoothers (P. A. Cornillon, A. Gribinski, N. Hengartner, T. Kerdreux and E. Matzner-Løber) -- Multiplicative Bias Corrected Nonparametric Smoothers (N. Hengartner, E. Matzner-Løber, L. Rouvière and T. Burr) -- Nonparametric PU Learning of State Estimation in Markov Switching Model (A. Dobrovidov and V. Vasilyev) -- Nonparametric Lower Bounds and Information Functions (S. Y. Novak) -- Efficiency of the V-fold Model Selection for Localized Bases (F. Navarro and A. Saumard) -- Modification of Moment-based Tail Index Estimator: Sums versus Maxima (N. Markovich and M. Vaičiulis) -- Constructing Confidence Sets for the Matrix Completion Problem (A. Carpentier, O. Klopp and M. Löffler) -- PAC-Bayesian Aggregation of Affine Estimators (L. Montuelle and E. Le Pennec) -- A Nonparametric Classification Algorithm Based on Optimized Templates (J. Kalina) -- Light- and Heavy-tailed Density Estimation by Gamma-Weibull Kernel (L. Markovich) -- Adaptive Estimation of Heavy Tail Distributions with Application to Hall Model (D. N. Politis, V. A. Vasiliev, S. E. Vorobeychikov) -- Extremal Index for a Class of Heavy-tailed Stochastic Processes in Risk Theory (C. Tillier) -- Elemental Estimates, Influence, and Algorithmic Leveraging (K. Knight) -- Bootstrapping Nonparametric M-Smoothers with Independent Error Terms (M. Maciak) -- Probability Bounds for Active Learning in the Regression Problem (A. K. Fermin and C. Ludeña) -- Subsampling for Big Data: Some Recent Advances (P. Bertail, O. Jelassi, J. Tressou and M. Zetlaoui) -- Extension Sampling Designs for Big Networks: Application to Twitter (A. Rebecq) -- Strong Separability in Circulant SSA (J. Bógalo, P. Poncela and E. Senra) -- Selection of Window Length in Singular Spectrum Analysis of a Time Series (P. Unnikrishnan and V. Jothiprakash) -- Fourier-type Monitoring Procedures for Strict Stationarity (S. Lee, S. G. Meintanis and C. Pretorius) -- Wavelet Whittle Estimation in Multivariate Time Series Models: Application to fMRI Data (S. Achard and I. Gannaz) -- On Kernel Smoothing with Gaussian Subordinated Spatial Data (S. Ghosh) -- Nonparametric and Parametric Methods for Change-Point Detection in Parametric Models (G. Ciuperca) -- Variance Estimation Free Tests for Structural Changes in Regression (B. Peštová and M. Pešta) -- Index. |
| Record Nr. | UNINA-9910315360203321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||