Big Data Analytics and Information Science for Business and Biomedical Applications
The analysis of Big Data in biomedical as well as business and financial research has drawn much attention from researchers worldwide. This book provides a platform for the deep discussion of state-of-the-art statistical methods developed for the analysis of Big Data in these areas. Both applied and...
محفوظ في:
| التنسيق: | Online |
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| اللغة: | الإنجليزية |
| منشور في: |
MDPI - Multidisciplinary Digital Publishing Institute
2022
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| الموضوعات: | |
| الوصول للمادة أونلاين: | ONIX_20220321_9783036531939_28 |
| الوسوم: |
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| _version_ | 1869518702714552320 |
|---|---|
| collection | Directory of Open Access Books |
| description | The analysis of Big Data in biomedical as well as business and financial research has drawn much attention from researchers worldwide. This book provides a platform for the deep discussion of state-of-the-art statistical methods developed for the analysis of Big Data in these areas. Both applied and theoretical contributions are showcased. |
| format | Online |
| id | doab-20.500.12854ir-79592 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-795922024-04-01T23:19:19Z Big Data Analytics and Information Science for Business and Biomedical Applications Ahmed, S. Ejaz Nathoo, Farouk high-dimensional nonlocal prior strong selection consistency estimation consistency generalized linear models high dimensional predictors model selection stepwise regression deep learning financial time series causal and dilated convolutional neural networks nuisance post-selection inference missingness mechanism regularization asymptotic theory unconventional likelihood high dimensional time-series segmentation mixture regression sparse PCA entropy-based robust EM information complexity criteria high dimension multicategory classification DWD sparse group lasso L2-consistency proximal algorithm abdominal aortic aneurysm emulation Medicare data ensembling high-dimensional data Lasso elastic net penalty methods prediction random subspaces ant colony system bayesian spatial mixture model inverse problem nonparamteric boostrap EEG/MEG data feature representation feature fusion trend analysis text mining thema EDItEUR::N History and Archaeology::NH History thema EDItEUR::J Society and Social Sciences::JB Society and culture: general::JBF Social and ethical issues The analysis of Big Data in biomedical as well as business and financial research has drawn much attention from researchers worldwide. This book provides a platform for the deep discussion of state-of-the-art statistical methods developed for the analysis of Big Data in these areas. Both applied and theoretical contributions are showcased. 2022-03-21T16:27:25Z 2022-03-21T16:27:25Z 2022 book ONIX_20220321_9783036531939_28 9783036531939 9783036531922 https://directory.doabooks.org/handle/20.500.12854/79592 eng image/jpeg Attribution 4.0 International https://mdpi.com/books/pdfview/book/4975 https://mdpi.com/books/pdfview/book/4975 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-3192-2 10.3390/books978-3-0365-3192-2 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036531939 9783036531922 246 Basel open access |
| spellingShingle | high-dimensional nonlocal prior strong selection consistency estimation consistency generalized linear models high dimensional predictors model selection stepwise regression deep learning financial time series causal and dilated convolutional neural networks nuisance post-selection inference missingness mechanism regularization asymptotic theory unconventional likelihood high dimensional time-series segmentation mixture regression sparse PCA entropy-based robust EM information complexity criteria high dimension multicategory classification DWD sparse group lasso L2-consistency proximal algorithm abdominal aortic aneurysm emulation Medicare data ensembling high-dimensional data Lasso elastic net penalty methods prediction random subspaces ant colony system bayesian spatial mixture model inverse problem nonparamteric boostrap EEG/MEG data feature representation feature fusion trend analysis text mining thema EDItEUR::N History and Archaeology::NH History thema EDItEUR::J Society and Social Sciences::JB Society and culture: general::JBF Social and ethical issues Big Data Analytics and Information Science for Business and Biomedical Applications |
| title | Big Data Analytics and Information Science for Business and Biomedical Applications |
| title_full | Big Data Analytics and Information Science for Business and Biomedical Applications |
| title_fullStr | Big Data Analytics and Information Science for Business and Biomedical Applications |
| title_full_unstemmed | Big Data Analytics and Information Science for Business and Biomedical Applications |
| title_short | Big Data Analytics and Information Science for Business and Biomedical Applications |
| title_sort | big data analytics and information science for business and biomedical applications |
| topic | high-dimensional nonlocal prior strong selection consistency estimation consistency generalized linear models high dimensional predictors model selection stepwise regression deep learning financial time series causal and dilated convolutional neural networks nuisance post-selection inference missingness mechanism regularization asymptotic theory unconventional likelihood high dimensional time-series segmentation mixture regression sparse PCA entropy-based robust EM information complexity criteria high dimension multicategory classification DWD sparse group lasso L2-consistency proximal algorithm abdominal aortic aneurysm emulation Medicare data ensembling high-dimensional data Lasso elastic net penalty methods prediction random subspaces ant colony system bayesian spatial mixture model inverse problem nonparamteric boostrap EEG/MEG data feature representation feature fusion trend analysis text mining thema EDItEUR::N History and Archaeology::NH History thema EDItEUR::J Society and Social Sciences::JB Society and culture: general::JBF Social and ethical issues |
| topic_facet | high-dimensional nonlocal prior strong selection consistency estimation consistency generalized linear models high dimensional predictors model selection stepwise regression deep learning financial time series causal and dilated convolutional neural networks nuisance post-selection inference missingness mechanism regularization asymptotic theory unconventional likelihood high dimensional time-series segmentation mixture regression sparse PCA entropy-based robust EM information complexity criteria high dimension multicategory classification DWD sparse group lasso L2-consistency proximal algorithm abdominal aortic aneurysm emulation Medicare data ensembling high-dimensional data Lasso elastic net penalty methods prediction random subspaces ant colony system bayesian spatial mixture model inverse problem nonparamteric boostrap EEG/MEG data feature representation feature fusion trend analysis text mining thema EDItEUR::N History and Archaeology::NH History thema EDItEUR::J Society and Social Sciences::JB Society and culture: general::JBF Social and ethical issues |
| url | ONIX_20220321_9783036531939_28 |