Extending the State-Space Model to Accommodate Missing Values in Responses and Covariates
允许响应与协变量缺失的扩展状态空间模型
This article proposes an extended state-space model for accommodating multivariate panel data. The novel aspect of this contribution is an adjustment to the classical model for multiple subjects that allows missingness in the covariates in addition to the responses. Missing covariate data are handled by a second state-space model nested inside the first to represent unobserved exogenous information. Relevant Kalman filter equations are derived, and explicit expressions are…