Exact Likelihood of Vector Autoregressive-Moving Average Process with Missing or Aggregated Data
存在缺失或聚合数据时向量ARMA过程的精确似然
This note points out that by using the Kalman filter with nonconstant coefficients, we can compute the exact likelihood of an autoregressive-moving average process observed with noise, when some of our observations are either missing or aggregated.