Table 5.

Average of mean posterior ± 1 s.d. over 10 different datasets for $\mathit{\alpha }$ and $\mathit{\sigma }$ using a Metropolis–Hastings algorithm

$\mathrm{\Delta }$	KF	$\mathit{\alpha }$	$\mathit{\sigma }$
0.1	KF1	$3.081\pm 0.258$	$1.670\pm 0.209$
0.5	KF1	$1.956\pm 0.153$	$1.199\pm 0.125$
1.0	KF1	$1.493\pm 0.112$	$0.799\pm 0.088$
2.0	KF1	$1.064\pm 0.090$	$0.485\pm 0.046$
0.1	KF2	$4.171\pm 0.417$	$1.974\pm 0.208$
0.5	KF2	$4.121\pm 0.377$	$2.068\pm 0.257$
1.0	KF2	$4.123\pm 0.445$	$2.083\pm 0.283$
2.0	KF2	$4.208\pm 0.783$	$2.091\pm 0.371$

Data were simulated from an OU process with $\mathit{\alpha }=4$ and $\mathit{\sigma }=2$