Improved Prediction and Network Estimation Using the Monotone Single Index Multi-variate Autoregressive Model
使用单调单指标多元自回归模型改进预测与网络估计
Network estimation from multi-variate point process or time series data is a problem of fundamental importance. Prior work has focused on parametric approaches that require a known parametric model, which makes estimation procedures less robust to model mis-specification, non-linearities and heterogeneities. In this paper, we develop a semi-parametric approach based on the monotone single-index multi-variate autoregressive model (SIMAM) which addresses these challenges. We…