Results 1 to 10 of about 4,304 (251)
A high throughput generative vector autoregression model for stochastic synapses [PDF]
Frontiers in Neuroscience, 2022 By imitating the synaptic connectivity and plasticity of the brain, emerging electronic nanodevices offer new opportunities as the building blocks of neuromorphic systems.
Tyler Hennen +7 more
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The Knowledge Analysis of Panel Vector Autoregression: A Systematic Review
SAGE Open, 2023 The panel vector autoregression (PVAR) model preserves the advantages of the vector autoregression model while expanding its time series to the spatial direction, which can effectively solve the problem of individual heterogeneity using panel data. It is
Rui Yang +3 more
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Annals of Statistics, 2017 We consider here a large-scale social network with a continuous response observed for each node at equally spaced time points. The responses from different nodes constitute an ultra-high dimensional vector, whose time series dynamic is to be investigated.
Xuening Zhu, Rui Pan, Guodong Li
exaly +5 more sources
A vector autoregression weather model for electricity supply and demand modeling
Journal of Modern Power Systems and Clean Energy, 2018 Weather forecasting is crucial to both the demand and supply sides of electricity systems. Temperature has a great effect on the demand side. Moreover, solar and wind are very promising renewable energy sources and are, thus, important on the supply side.
Yixian LIU +2 more
doaj +3 more sources
Vector autoregression, structural equation modeling, and their synthesis in neuroimaging data analysis [PDF]
Computers in Biology and Medicine, 2011 Daniel Glen +2 more
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Heteroskedastic Proxy Vector Autoregressions [PDF]
SSRN Electronic Journal, 2020 In proxy vector autoregressive models, the structural shocks of interest are identified by an instrument. Although heteroskedasticity is occasionally allowed for, it is typically taken for granted that the impact effects of the structural shocks are time-invariant despite the change in their variances. We develop a test for this implicit assumption and
Lütkepohl, Helmut, Schlaak, Thore
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Reexamining Phillips curve: An empirical analysis from Structural Vector Autoregression [PDF]
Industrija, 2021 In the literature, the existence of the Phillips curve in every country has been extensively explored. The goal of this research is to investigate the inflation-unemployment trade-off in Indonesia.
Sasongko Gatot +3 more
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Nonlinear vector autoregressions in short-term metal price forecasting
π-Economy, 2023 In order to make an effective economic decision, it is necessary to have an idea of the possible future state of the decision-making object and its environment, which is obtained by means of forecasting.
Svetunkov Sergey, Samarina Elizaveta
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Markov-Switching Bayesian Vector Autoregression Model in Mortality Forecasting
Risks, 2023 We apply a Markov-switching Bayesian vector autoregression (MSBVAR) model to mortality forecasting. MSBVAR has not previously been applied in this context, and our results show that it is a promising tool for mortality forecasting. Our model shows better
Wanying Fu +3 more
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Noncausal Vector Autoregression [PDF]
SSRN Electronic Journal, 2009 In this paper, we propose a new noncausal vector autoregressive (VAR) model for non-Gaussian time series. The assumption of non-Gaussianity is needed for reasons of identifiability. Assuming that the error distribution belongs to a fairly general class of elliptical distributions, we develop an asymptotic theory of maximum likelihood estimation and ...
Lanne, Markku, Saikkonen, Pentti
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