Network Vector Autoregressive Model for Dyadic Response Variables

05/29/2022
by   Jiajia Wang, et al.
0

For general panel data, by introducing network structure, network vector autoregressive (NVAR) model captured the linear inter dependencies among multiple time series. In this paper, we propose network vector autoregressive model for dyadic response variables (NVARD), which describes the dynamic process of dyadic data in the case of the dependencies among different pairs are taken into consideration. Besides, due to the existence of heterogeneity between time and individual, we propose time-varying coefficient network vector autoregressive model for dyadic response variables (VCNVARD). Finally, we apply these models to predict world bilateral trade flows.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
11/14/2017

How to estimate time-varying Vector Autoregressive Models? A comparison of two methods

The ubiquity of mobile devices led to a surge in intensive longitudinal ...
research
05/17/2020

Simultaneous and Temporal Autoregressive Network Models

While logistic regression models are easily accessible to researchers, w...
research
05/05/2020

Arctic Amplification of Anthropogenic Forcing: A Vector Autoregressive Analysis

Arctic sea ice extent (SIE) in September 2019 ranked second-to-lowest in...
research
06/29/2020

Inference in Bayesian Additive Vector Autoregressive Tree Models

Vector autoregressive (VAR) models assume linearity between the endogeno...
research
05/09/2016

Inference of High-dimensional Autoregressive Generalized Linear Models

Vector autoregressive models characterize a variety of time series in wh...
research
10/20/2016

Nonlinear Structural Vector Autoregressive Models for Inferring Effective Brain Network Connectivity

Structural equation models (SEMs) and vector autoregressive models (VARM...
research
07/12/2023

COVID-19 incidence in the Republic of Ireland: A case study for network-based time series models

Network-based Time Series models have experienced a surge in popularity ...

Please sign up or login with your details

Forgot password? Click here to reset