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

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

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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.

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Keywords

  • asymptotic bias and risk
  • bandwidth selection
  • Bayesian modeling
  • big data adaptation
  • Brain Network
  • Cancer
  • causal structure learning
  • chest X-ray images
  • Computer science
  • Computing & information technology
  • consistency
  • correlation
  • deep learning
  • dividend estimation
  • Economics, finance, business & 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 & 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, information & 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

Links

DOI: 10.3390/books978-3-0365-5550-8

Editions

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