Table 3.

The prior information about the Bayesian probabilistic constraint model.

Parameter	Knot	N	D1	D2	D3	D4	Mean	Alpha	Beta
θ 1	P2.5	4	0.3	0.5	0.7	0.3	0.450	75.83	66.73
	P97.5	4	0.55	0.7	0.8	0.4	0.613
θ 2	P2.5	4	0.9	0.7	0.8	0.6	0.572	70.84	35.86
	P97.5	4	0.99	0.8	0.9	0.8	0.750
θ 3	P2.5	4	0.7	0.7	0.7	0.8	0.417	21.90	16.21
	P97.5	4	0.8	0.8	0.8	0.9	0.725
θ 4	P2.5	4	0.7	0.4	0.4	0.75	0.563	99.74	56.18
	P97.5	4	0.8	0.6	0.6	0.85	0.713
θ 5	P2.5	4	0.3	0.3	0.4	0.1	0.275	53.43	100.05
	P97.5	4	0.5	0.5	0.5	0.2	0.425
θ 6	P2.5	4	0.7	0.4	0.4	0.75	0.563	143.25	85.38
	P97.5	4	0.8	0.6	0.5	0.85	0.688
θ 7	P2.5	4	0.2	0.3	0.6	0.5	0.400	112.32	130.69
	P97.5	4	0.3	0.5	0.7	0.6	0.525

D1: Doctor 1; D2: Doctor 2; D3: Doctor 3; D4: Doctor4. Alpha and Beta are two parameters of the beta distribution.