03251nam 2200949z- 450 991055761480332120231214133400.0(CKB)5400000000045254(oapen)https://directory.doabooks.org/handle/20.500.12854/79592(EXLCZ)99540000000004525420202203d2022 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierBig Data Analytics and Information Science for Business and Biomedical ApplicationsBaselMDPI - Multidisciplinary Digital Publishing Institute20221 electronic resource (246 p.)3-0365-3193-9 3-0365-3192-0 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.HumanitiesbicsscSocial interactionbicsschigh-dimensionalnonlocal priorstrong selection consistencyestimation consistencygeneralized linear modelshigh dimensional predictorsmodel selectionstepwise regressiondeep learningfinancial time seriescausal and dilated convolutional neural networksnuisancepost-selection inferencemissingness mechanismregularizationasymptotic theoryunconventional likelihoodhigh dimensional time-seriessegmentationmixture regressionsparse PCAentropy-based robust EMinformation complexity criteriahigh dimensionmulticategory classificationDWDsparse group lassoL2-consistencyproximal algorithmabdominal aortic aneurysmemulationMedicare dataensemblinghigh-dimensional dataLassoelastic netpenalty methodspredictionrandom subspacesant colony systembayesian spatial mixture modelinverse problemnonparamteric boostrapEEG/MEG datafeature representationfeature fusiontrend analysistext miningHumanitiesSocial interactionAhmed S. Ejazedt1062202Nathoo FaroukedtAhmed S. EjazothNathoo FaroukothBOOK9910557614803321Big Data Analytics and Information Science for Business and Biomedical Applications3027101UNINA