03268nam 2200961z- 450 991055761480332120220321(CKB)5400000000045254(oapen)https://directory.doabooks.org/handle/20.500.12854/79592(oapen)doab79592(EXLCZ)99540000000004525420202203d2022 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierBig Data Analytics and Information Science for Business and Biomedical ApplicationsBaselMDPI - Multidisciplinary Digital Publishing Institute20221 online 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 interactionbicsscabdominal aortic aneurysmant colony systemasymptotic theorybayesian spatial mixture modelcausal and dilated convolutional neural networksdeep learningDWDEEG/MEG dataelastic netemulationensemblingentropy-based robust EMestimation consistencyfeature fusionfeature representationfinancial time seriesgeneralized linear modelshigh dimensionhigh dimensional predictorshigh dimensional time-serieshigh-dimensionalhigh-dimensional datainformation complexity criteriainverse problemL2-consistencyLassoMedicare datamissingness mechanismmixture regressionmodel selectionmulticategory classificationnonlocal priornonparamteric boostrapnuisancepenalty methodspost-selection inferencepredictionproximal algorithmrandom subspacesregularizationsegmentationsparse group lassosparse PCAstepwise regressionstrong selection consistencytext miningtrend analysisunconventional likelihoodHumanitiesSocial interactionAhmed S. Ejazedt1062202Nathoo FaroukedtAhmed S. EjazothNathoo FaroukothBOOK9910557614803321Big Data Analytics and Information Science for Business and Biomedical Applications3027101UNINA