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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.

Information technology industries --- Computer science --- bandwidth selection --- correlation --- edge-preserving image denoising --- image sequence --- jump regression analysis --- local smoothing --- nonparametric regression --- spatio-temporal data --- linear mixed model --- ridge estimation --- pretest and shrinkage estimation --- multicollinearity --- asymptotic bias and risk --- LASSO estimation --- high-dimensional data --- big data adaptation --- dividend estimation --- options markets --- weighted least squares --- online health community --- social support --- network analysis --- cancer --- functional principal component analysis --- functional predictor --- linear mixed-effects model --- mobile device --- sparse group regularization --- wearable device data --- Bayesian modeling --- functional regression --- gestational weight --- infant birth weight --- joint modeling --- longitudinal data --- maternal weight gain --- transfer learning --- deep learning --- pretrained neural networks --- chest X-ray images --- lung diseases --- causal structure learning --- consistency --- FCI algorithm --- high dimensionality --- nonparametric testing --- PC algorithm --- fMRI --- functional connectivity --- brain network --- Human Connectome Project --- statistics