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Applied multivariate statistical analysis / Wolfgang Karl Hardle, Léopold Simar
| Applied multivariate statistical analysis / Wolfgang Karl Hardle, Léopold Simar |
| Autore | Härdle, Wolfgang Karl |
| Edizione | [5. ed] |
| Pubbl/distr/stampa | Cham, : Springer, 2019 |
| Descrizione fisica | xii, 558 p. : ill. ; 24 cm |
| Altri autori (Persone) | Simar, Léopold |
| Soggetto topico |
62H12 - Estimation in multivariate analysis [MSC 2020]
62H25 - Factor analysis and principal components; correspondence analysis [MSC 2020] 62H30 - Classification and discrimination; cluster analysis (statistical aspects) [MSC 2020] 62H17 - Contingency tables [MSC 2020] 62H15 - Hypothesis testing in multivariate analysis [MSC 2020] 62H20 - Measures of association (correlation, canonical correlation, etc.) [MSC 2020] 62H10 - Multivariate distribution of statistics [MSC 2020] 62F25 - Parametric tolerance and confidence regions [MSC 2020] |
| Soggetto non controllato |
Applications in Finance
Big data analysis Cluster analysis Clustering Computationally Intensive Techniques Conjoint Measurement Analysis Dimension Reduction Techniques Discriminant Analysis Hypothesis Testing Lasso and Elastic Net Multivariate Classification Multivariate data analysis Projection Persuit Quantitative Finance Sliced Inverse Regression Variable Selection |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0126731 |
Härdle, Wolfgang Karl
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| Cham, : Springer, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Applied multivariate statistical analysis / Wolfgang Karl Hardle, Léopold Simar
| Applied multivariate statistical analysis / Wolfgang Karl Hardle, Léopold Simar |
| Autore | Härdle, Wolfgang Karl |
| Edizione | [4. ed] |
| Pubbl/distr/stampa | Berlin ; Heidelberg, : Springer, 2015 |
| Descrizione fisica | XIII, 580 p. : ill. ; 24 cm |
| Altri autori (Persone) | Simar, Léopold |
| Soggetto topico |
62H12 - Estimation in multivariate analysis [MSC 2020]
62H25 - Factor analysis and principal components; correspondence analysis [MSC 2020] 62H30 - Classification and discrimination; cluster analysis (statistical aspects) [MSC 2020] 62H17 - Contingency tables [MSC 2020] 62H15 - Hypothesis testing in multivariate analysis [MSC 2020] 62H20 - Measures of association (correlation, canonical correlation, etc.) [MSC 2020] 62H10 - Multivariate distribution of statistics [MSC 2020] 62F25 - Parametric tolerance and confidence regions [MSC 2020] |
| Soggetto non controllato |
Cluster analysis
Conjoint Measurement Analysis Discriminant Analysis Elastic Net Hypothesis Testing Lasso Multivariate Analysis Projection Persuit Quantitative Finance Sliced Inverse Regression |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0113928 |
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Härdle, Wolfgang Karl
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| Berlin ; Heidelberg, : Springer, 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Machine Learning Methods with Noisy, Incomplete or Small Datasets
| Machine Learning Methods with Noisy, Incomplete or Small Datasets |
| Autore | Solé-Casals Jordi |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (316 p.) |
| Soggetto topico | Information technology industries |
| Soggetto non controllato |
open contours
similarly shaped fish species Discrete Cosine Transform (DCT) Discrete Fourier Transform (DFT) Extreme Learning Machines (ELM) feature engineering small data-sets optimization machine learning preprocessing image generation weighted interpolation map binarization single sample per person root canal measurement multifrequency impedance data augmentation neural network functional magnetic resonance imaging independent component analysis deep learning recurrent neural network functional connectivity episodic memory small sample learning feature selection noise elimination space consistency label correlations empirical mode decomposition sparse representations tensor decomposition tensor completion machine translation pairwise evaluation educational data small datasets noisy datasets smart building Internet of Things (IoT) Markov Chain Monte Carlo (MCMC) ontology graph model Artificial Neural Network Discriminant Analysis dengue feature extraction sound event detection non-negative matrix factorization ultrasound images shadow detection shadow estimation auto-encoders semi-supervised learning prediction feature importance feature elimination hierarchical clustering Parkinson’s disease few-shot learning permutation-variable importance topological data analysis persistent entropy support-vector machine data science intelligent decision support social vulnerability gender-gap digital-gap COVID19 policy-making support artificial intelligence imperfect dataset |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557324603321 |
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Solé-Casals Jordi
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Robust Multivariate Analysis / David J. Olive
| Robust Multivariate Analysis / David J. Olive |
| Autore | Olive, David J. |
| Pubbl/distr/stampa | Cham, : Springer, 2017 |
| Descrizione fisica | xvi, 501 p. : ill. ; 24 cm |
| Soggetto topico |
62Hxx - Multivariate analysis [MSC 2020]
62G35 - Nonparametric robustness [MSC 2020] |
| Soggetto non controllato |
Bootstrap Confidence Region
Canonical Correlation Analysis Discriminant Analysis MANOVA Multivariate Regression Prediction Region Principal component analysis Robust Statistics |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0124177 |
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Olive, David J.
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| Cham, : Springer, 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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