TABLE 1.

Simulation results, regression of $\widehat{\mathit{h}}$ on h for MFVB vs. MCMC

AR-1	Method	Time window	Intercept	Slope	R2	RMSE
0.8	MFVB	1	0.02	N/A	N/A	0.24
		2	0.00	0.89	0.97	0.23
		3	0.00	0.97	0.99	0.22
		4	−0.01	0.99	0.99	0.22
	MCMC	1	0.05	N/A	N/A	0.26
		2	0.01	0.91	0.96	0.26
		3	−0.02	0.98	0.99	0.24
		4	−0.04	1.00	0.99	0.22
0.5	MFVB	1	0.01	N/A	N/A	0.20
		2	0.00	0.92	0.97	0.25
		3	0.00	0.97	0.99	0.27
		4	0.01	0.99	0.99	0.22
	MCMC	1	0.06	N/A	N/A	0.23
		2	0.02	0.93	0.96	0.25
		3	−0.02	0.97	0.98	0.27
		4	−0.04	1.00	0.99	0.23
0.2	MFVB	1	0.04	N/A	N/A	0.22
		2	0.00	0.92	0.97	0.24
		3	−0.01	0.96	0.99	0.22
		4	−0.01	0.98	0.99	0.24
	MCMC	1	0.06	N/A	N/A	0.24
		2	0.01	0.93	0.97	0.24
		3	−0.02	0.96	0.99	0.22
		4	−0.04	0.98	0.99	0.23

Performance of estimated h_t (z_i,_t) across 100 simulated datasets, each with N = 300. RMSE denotes the root mean squared error of the $\widehat{\mathit{h}}$ as compared to h. Coverage denotes the proportion of times that the true h falls within in the 95% posterior credible interval of each time point. At time window 1, there is no effect; thus, slope and R² are not applicable to the regression of $\widehat{\mathit{h}}$ on h.