Robust Expectation-Maximization for Covariance Estimation in SIRV Models with Missing Data: Application to InSAR Time Series
缺失数据 SIRV 模型中的稳健 EM 协方差估计及 InSAR 时间序列应用
This paper presents a robust Expectation-Maximization framework for covariance estimation in Scale-Invariant Random Vector (SIRV) models with missing data under ignorable missingness mechanisms. By adopting an inverse-gamma prior on the scale variables, the resulting observation model leads to a complex multivariate Student-t distribution and allows closed-form E-step and M-step updates. The proposed algorithm incorporates numerical robustness techniques such as computation…