Table 7.

Estimates of parameters and their standard deviations (in parentheses) based on the MCMC algorithm for the data simulated under scenario 3.

	ϕ	θ	r	pa	pb	da	db	Dab	Da/b	Dab	Dab	dab
SAMPLING STRATEGY 1: 1000 × 9
True	0.87	0.72	0.2	0.5	0.6	0.05	0.05	0.1	0.01	0.01	0.01	0.01
Estimate	0.871	0.724	0.192	0.500	0.599	0.050	0.099	0.011	0.010	0.010	0.010	0.010
SD	(0.036)	(0.011)	(0.049)	(0.009)	(0.008)	(0.010)	(0.007)	(0.003)	(0.009)	(0.003)	(0.003)	(0.002)
SAMPLING STRATEGY 2: 200 × 49
True	0.87	0.72	0.2	0.5	0.6	0.05	0.05	0.1	0.01	0.01	0.01	0.01
Estimate	0.866	0.726	0.154	0.500	0.599	0.049	0.050	0.098	0.011	0.010	0.010	0.010
SD	(0.085)	(0.018)	(0.500)	(0.028)	(0.027)	(0.027)	(0.017)	(0.004)	(0.021)	(0.006)	(0.006)	(0.004)