Results 191 to 200 of about 3,856 (236)
Clustering matrix-object data by correlational structure as proxy causal signals. [PDF]
Sci RepQi Z, Yu L, Li J.
europepmc +1 more source
Scoping review of artificial intelligence via mobile technology and social media for health in Africa. [PDF]
Nat CommunBaichoo S +7 more
europepmc +1 more source
Dynamic interactions of COVID-19 incidences, mobility, and social distancing policies in seoul: A VAR model approach. [PDF]
Sci RepHu Z, Chang W, Jang Y, Jo Y, Jung J.
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Vector autoregression and envelope model
Stat, 2018 Vector autoregression is an important technique for modelling multivariate time series and has been widely used in a variety of applications. Owing to its fast growth of parameters with the dimension of the time series vector, dimension reduction is often desirable in multivariate time series analysis.
Lei Wang, Shanshan Ding, Shanshan Ding
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Modelling of cointegration in the vector autoregressive model
Economic Modelling, 2000Abstract A survey is given of some results obtained for the cointegrated VAR. The Granger representation theorem is discussed and the notions of cointegration and common trends are defined. The statistical model for cointegrated I (1) variables is defined, and it is shown how hypotheses on the cointegrating relations can be estimated under suitable ...
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2017 3rd International Conference on Big Data Computing and Communications (BIGCOM), 2017
VAR (Vector Auto-regressive) model is a kind of commonly used econometric-model. It is used to estimate the dynamic relationship of the endogenous variables without any prior constraints. Since VAR is one of the most easily operated models to deal with the analysis and prediction of multiple related economic indicators, more and more attention has been
Tao Li, Xueyu Li, Xu Zhang
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VAR (Vector Auto-regressive) model is a kind of commonly used econometric-model. It is used to estimate the dynamic relationship of the endogenous variables without any prior constraints. Since VAR is one of the most easily operated models to deal with the analysis and prediction of multiple related economic indicators, more and more attention has been
Tao Li, Xueyu Li, Xu Zhang
openaire +2 more sources
Process Control for the Vector Autoregressive Model
Quality and Reliability Engineering International, 2012Multivariate monitoring techniques for serially correlated observations have been widely used in various applications. This study examines several issues that have arisen in relation to the statistical quality control for the vector autoregressive (VAR) model, using a Monte Carlo approach.
Cheng, T.-C., Hsieh, P.-H., Yang, S.-F.
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Order selection for vector autoregressive models
IEEE Transactions on Signal Processing, 2003Order-selection criteria for vector autoregressive (AR) modeling are discussed. The performance of an order-selection criterion is optimal if the model of the selected order is the most accurate model in the considered set of estimated models: here vector AR models. Suboptimal performance can be a result of underfit or overfit.
de Waele, S. (author) +1 more
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