EURASIP Journal on Advances in Signal Processing

Table 9 MSEs in estimation of R and Ω using FUSS and MH inside a Gibbs sampler, with δ=10⁻³, K=10, and N_G=50, for the example of Section 6.3

From: A survey of Monte Carlo methods for parameter estimation

		λ=0.001	λ=0.005	λ=0.01	λ=0.05	λ=0.08	λ=0.10
FUSS	MSE(R)	0.0071	0.0089	0.0093	0.0138	0.0150	0.0778
	MSE(Ω)	5.01 10⁻⁵	6.15 10⁻⁵	6.15 10⁻⁵	5.26 10⁻⁵	7.33 10⁻⁵	1.78 10⁻⁴
MH (σ_p=1)	MSE(R)	0.6830	0.7264	0.7067	1.1631	1.3298	1.3293
	MSE(Ω)	0.0373	0.0402	0.0423	0.0399	0.0471	0.0440
MH (σ_p=2)	MSE(R)	1.3566	1.4906	1.4247	2.0015	2.3042	2.2401
	MSE(Ω)	0.0897	0.1117	0.1041	0.0989	0.1089	0.1125

The observed sequence, z_1:T, is generated with R=3.7, Ω=0.4, and N=20 and different values of λ

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