From: Sequential Monte Carlo for inference of latent ARMA time-series with innovations correlated in time
PF type | State estimation error (MSE) | |||||
---|---|---|---|---|---|---|
Known a,b | Known a,b | Unknown a,b, DA | Unknown a,b,, IS | Unknown a,b, DA | Unknown a,b IS | |
Known \(\sigma _{u}^{2}\) | Unknown \(\sigma _{u}^{2}\) | Known \(\sigma _{u}^{2}\) | Known \(\sigma _{u}^{2}\) | Unknown \(\sigma _{u}^{2}\) | Unknown \(\sigma _{u}^{2}\) | |
AR(1), H=0.5 | 1.0991 | 1.127 | 1.6689 | 1.7337 | 1.4549 | 1.5903 |
AR(1), H=0.7 | 1.4077 | 1.4375 | 2.5759 | 5.9889 | 1.9272 | 3.191 |
AR(1), H=0.9 | 1.1336 | 1.1774 | 2.4334 | 6.5974 | 1.7795 | 6.4853 |
MA(1), H=0.5 | 1.0348 | 1.0758 | 1.1033 | 1.185 | 1.1384 | 1.3831 |
MA(1), H=0.7 | 1.0878 | 1.1138 | 1.1857 | 1.2688 | 1.1884 | 1.3748 |
MA(1), H=0.9 | 0.88045 | 0.90841 | 0.96348 | 1.1124 | 0.97747 | 1.2517 |
ARMA(1,1), H=0.5 | 1.638 | 1.6512 | 2.8563 | 3.6266 | 2.3157 | 2.3619 |
ARMA(1,1), H=0.7 | 1.7452 | 1.7926 | 3.0939 | 4.1174 | 2.7807 | 2.4627 |
ARMA(1,1), H=0.9 | 1.7374 | 1.7533 | 4.3466 | 20.617 | 2.5818 | 2.569 |