Handling missing data in multivariate time series using a vector autoregressive model-imputation (VAR-IM) algorithm

Neurocomputing

Volumn 276, Issue , 2018, Pages 23-30

  Bashir, Faraj ^a   Wei, Hua Liang ^b,c  

^a University of Shffield   (United Kingdom)

^b University of Shffield   (United Kingdom)

^c CISTIB Centre for Computational Imaging and Simulation Technologies in Biomedicine INSIGNEO Institute for in silico Medicine Department of Mechanical Engineering The University of Sheffield   (United Kingdom)

Author keywords

ECG; EM algorithm; Missing data; VAR model

Indexed keywords

DATA HANDLING; ELECTROCARDIOGRAPHY; IMAGE SEGMENTATION; MAXIMUM PRINCIPLE; TIME SERIES; VALUE ENGINEERING;

EM ALGORITHMS; EXPECTATION-MAXIMIZATION ALGORITHMS; MISSING DATA; MULTIVARIATE TIME SERIES; PREDICTION ERROR MINIMIZATIONS; TIME-SERIES MODELLING; VAR MODELS; VECTOR AUTOREGRESSIVE MODEL;

TIME SERIES ANALYSIS;

ALGORITHM; ANALYTIC METHOD; ARTICLE; ELECTROCARDIOGRAM; INFORMATION PROCESSING; MAXIMUM LIKELIHOOD METHOD; PREDICTION; PRIORITY JOURNAL; PROCESS MODEL; QRS AMPLITUDE; TIME SERIES ANALYSIS; VECTOR AUTOREGRESSIVE MODEL IMPUTATION;

EID: 85029793560     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2017.03.097     Document Type: Article

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