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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.

Humanities --- Social interaction --- 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

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

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.

Humanities --- Social interaction --- 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