Big Data Analytics and Information Science for Business and Biomedical Applications

Open Access

Big Data Analytics and Information Science for Business and Biomedical Applications

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...

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HerausgeberIn:
Nathoo, Farouk
Sonstige:
Ahmed, S. Ejaz
Nathoo, Farouk
Year of Publication:2022
Language:English
Physical Description:1 electronic resource (246 p.)
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spelling Ahmed, S. Ejaz edt
Big Data Analytics and Information Science for Business and Biomedical Applications
Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
1 electronic resource (246 p.)
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Open access Unrestricted online access star
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.
English
Humanities bicssc
Social interaction bicssc
high-dimensional
nonlocal prior
strong selection consistency
estimation consistency
generalized linear models
high dimensional predictors
model selection
stepwise regression
deep learning
financial time series
causal and dilated convolutional neural networks
nuisance
post-selection inference
missingness mechanism
regularization
asymptotic theory
unconventional likelihood
high dimensional time-series
segmentation
mixture regression
sparse PCA
entropy-based robust EM
information complexity criteria
high dimension
multicategory classification
DWD
sparse group lasso
L2-consistency
proximal algorithm
abdominal aortic aneurysm
emulation
Medicare data
ensembling
high-dimensional data
Lasso
elastic net
penalty methods
prediction
random subspaces
ant colony system
bayesian spatial mixture model
inverse problem
nonparamteric boostrap
EEG/MEG data
feature representation
feature fusion
trend analysis
text mining
3-0365-3193-9
3-0365-3192-0
Nathoo, Farouk edt
Ahmed, S. Ejaz oth
Nathoo, Farouk oth
language English
format eBook
author2 Nathoo, Farouk
Ahmed, S. Ejaz
Nathoo, Farouk
author_facet Nathoo, Farouk
Ahmed, S. Ejaz
Nathoo, Farouk
author2_variant s e a se sea
f n fn
author2_role HerausgeberIn
Sonstige
Sonstige
title Big Data Analytics and Information Science for Business and Biomedical Applications
spellingShingle Big Data Analytics and Information Science for Business and Biomedical Applications
title_full Big Data Analytics and Information Science for Business and Biomedical Applications
title_fullStr Big Data Analytics and Information Science for Business and Biomedical Applications
title_full_unstemmed Big Data Analytics and Information Science for Business and Biomedical Applications
title_auth Big Data Analytics and Information Science for Business and Biomedical Applications
title_new Big Data Analytics and Information Science for Business and Biomedical Applications
title_sort big data analytics and information science for business and biomedical applications
publisher MDPI - Multidisciplinary Digital Publishing Institute
publishDate 2022
physical 1 electronic resource (246 p.)
isbn 3-0365-3193-9
3-0365-3192-0
illustrated Not Illustrated
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