Cover Image
Read Now

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

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 appl...

Full description

Bibliographic Details
Main Author: Ahmed, S. Ejaz
Other Authors: Nathoo, Farouk
Format: eBook
Language:English
Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
Subjects:
Local Smoothing
Bayesian Modeling
Consistency
Pc Algorithm
Bandwidth Selection
Chest X-ray Images
Edge-preserving Image Denoising
High Dimensionality
Joint Modeling
Options Markets
Mobile Device
Deep Learning
Jump Regression Analysis
Social Support
Pretest And Shrinkage Estimation
Image Sequence
Gestational Weight
Fci Algorithm
Spatio-temporal Data
Lasso Estimation
Longitudinal Data
High-dimensional Data
Functional Regression
Functional Connectivity
Dividend Estimation
Network Analysis
Maternal Weight Gain
Nonparametric Regression
Transfer Learning
Information Technology Industries / Bicssc
Sparse Group Regularization
Correlation
Pretrained Neural Networks
Asymptotic Bias And Risk
Computer Science / Bicssc
Multicollinearity
Cancer
Lung Diseases
Brain Network
Functional Principal Component Analysis
Fmri
Weighted Least Squares
Linear Mixed-effects Model
Statistics
Causal Structure Learning
Big Data Adaptation
Functional Predictor
Wearable Device Data
Linear Mixed Model
Nonparametric Testing
Human Connectome Project
Ridge Estimation
Infant Birth Weight
Online Health Community
Online Access:
Collection: Directory of Open Access Books - Collection details see MPG.ReNa
Description
Summary: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.
Item Description:Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
Physical Description:1 electronic resource (196 p.)
ISBN:9783036555492
books978-3-0365-5550-8
9783036555508

Similar Items