Bayesian Methods for Estimation the Parameters of Finite Mixture of Inverse Rayleigh Distribution

Table 1

This table shows the results of AMSE and ACSR of applying the three methods to simulated data by three different scenarios written at the top and three different of sample sizes with 1000 replications.

N	Method
		AMSE	ACSR	AMSE	ACSR	AMSE	ACSR	AMSE	ACSR
100	Gibbs	0.00179	0.8603	0.00226	0.7576	0.00124	0.8438	0.00292	0.7926
	MH	0.00157	0.7959	0.00263	0.6674	0.00118	0.7759	0.00298	0.7252
150	Gibbs	0.00172	0.8627	0.00219	0.753	0.00123	0.845	0.003	0.7875
	MH	0.00152	0.7953	0.00242	0.6718	0.00116	0.7746	0.00287	0.7327
200	Gibbs	0.00174	0.8654	0.00224	0.7398	0.00126	0.8529	0.00295	0.7982
	MH	0.00154	0.7992	0.00243	0.666	0.00118	0.78172	0.00284	0.7326