Big Data Analytics and Information Science for Business and Biomedical Applications II

The analysis of big data in biomedical, business and financial research has drawn much attention from researchers worldwide. This collection of articles aims to provide a platform for an in-depth discussion of novel statistical methods developed for the analysis of Big Data in these areas. Both appl...

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Format:	Buch
Sprache:	eng
Schlagworte:	asymptotic bias and risk bandwidth selection Bayesian modeling big data adaptation brain network cancer causal structure learning chest X-ray images Computer science Computing and Information Technology consistency correlation deep learning dividend estimation Economics, Finance, Business and Management edge-preserving image denoising FCI algorithm fMRI functional connectivity functional predictor functional principal component analysis functional regression gestational weight high dimensionality high-dimensional data Human Connectome Project image sequence Industry and industrial studies infant birth weight Information technology industries joint modeling jump regression analysis LASSO estimation linear mixed model linear mixed-effects model local smoothing longitudinal data lung diseases maternal weight gain Media, entertainment, information and communication industries mobile device multicollinearity network analysis nonparametric regression nonparametric testing online health community options markets PC algorithm pretest and shrinkage estimation pretrained neural networks ridge estimation social support sparse group regularization spatio-temporal data statistics transfer learning wearable device data weighted least squares
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Beschreibung
Zusammenfassung:	The analysis of big data in biomedical, business and financial research has drawn much attention from researchers worldwide. This collection of articles aims to provide a platform for an in-depth discussion of novel statistical methods developed for the analysis of Big Data in these areas. Both applied and theoretical contributions to these areas are showcased.
DOI:	10.3390/books978-3-0365-5550-8