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
doaj +3 more sources
Forecasting COVID-19: Vector Autoregression-Based Model. [PDF]
Arab J Sci Eng, 2022 Forecasting the spread of COVID-19 infection is an important aspect of public health management. In this paper, we propose an approach to forecasting the spread of the pandemic based on the vector autoregressive model.
Rajab K, Kamalov F, Cherukuri AK.
europepmc +2 more sources
Economic policy uncertainty, investor sentiment and financial stability-an empirical study based on the time varying parameter-vector autoregression model. [PDF]
J Econ Interact Coord, 2022 This paper applies the time varying parameter-vector autoregression model to explore the dynamic relationship between economic policy uncertainty, investor sentiment and financial stability in China in different periods and at different time points.
Qi XZ, Ning Z, Qin M.
europepmc +2 more sources
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 +6 more sources
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
doaj +2 more sources
Vector Autoregression Model-Based Forecasting of Reference Evapotranspiration in Malaysia
Sustainability, 2023 Evapotranspiration is one of the hydrological cycle’s most important elements in water management across economic sectors. Critical applications in the agriculture domain include irrigation practice improvement and efficiency, as well as water resource ...
Lokman Mohd Fadzil +2 more
exaly +2 more sources
Regional Photovoltaic Power Forecasting Using Vector Autoregression Model in South Korea
Energies, 2022 Renewable energy forecasting is a key for efficient resource use in terms of power generation and safe grid control. In this study, we investigated a short-term statistical forecasting model with 1 to 3 h horizons using photovoltaic operation data from ...
A-Hyun Jung +5 more
doaj +2 more sources
Bayesian Compressed Vector Autoregression for Financial Time-Series Analysis and Forecasting
IEEE Access, 2019 Advanced time series models have been intensively developed and used to predict in financial data such as foreign exchange data (forex). In this paper, we implement the random compression method to reduce a large dimensional forex data into much smaller ...
Paponpat Taveeapiradeecharoen +2 more
doaj +2 more sources
Modeling mortality with a Bayesian vector autoregression [PDF]
Insurance: Mathematics and Economics, 2020 Mortality risk models have been developed to capture trends and common factors driving mortality improvement. Multiple factor models take many forms and are often developed and fitted to older ages.
Carolyn Njenga, M. Sherris
semanticscholar +4 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 +2 more sources