Erev, I. et al. A Choice Prediction Competition for Market Entry Games: An Introduction. Games 2010, 1, 117-136

Ion Juvina found an error in our manuscript published in Games [1]. The error led to overestimation (by about 3%) of the alternation rate presented in Table 2 (in page 120). The correction does not change the main conclusions, but it slightly changes five exhibits. The corrected exhibits are presented below, and in the competition website (http://sites.google.com/site/gpredcomp).

Table 2. The 40 market entry games that were studied in the estimation experiment. At each trial, each of 4 players has to decide (individually) between “entering a risky market”, or “staying out” (a safer prospect). The payoffs depended on a realization of a binary gamble (the realization at trial t is denoted G_t, and yields “H with probability Ph; and L otherwise”), the number of entrants (E), and two additional parameters (k and S). The exact payoff for player i at trial t is: ${{\displaystyle V}}_i(t)=\left\{{}_{{\text{round(G}}_{\text{t}}\text{/S) with p=}{\text{.5; -round(G}}_{\text{t}}\text{/S) otherwise if i does not enter}}^{{\text{ 10-k(E)+G}}_{\text{t}}\text{ if i enters}}\right\}$ The left hand-columns present the exact value of the different parameters in the 40 games, the right hand columns present the equilibrium predictions, and the main experimental results in the first and second block (B1 and B2).

								Experimental results
The games						Entry at eq.		Entry rates		Efficiency		Alternations
#	K	ph	H	L	S	pure	symmetric	B1	B2	B1	B2	B1	B2
1	2	0.04	70	-3	5	1.00	1.00	0.71	0.80	2.77	2.66	0.16	0.16
2	2	0.23	30	-9	4	1.00	1.00	0.55	0.62	2.64	2.75	0.25	0.23
3	2	0.67	1	-2	3	1.00	1.00	0.88	0.94	2.39	2.24	0.10	0.04
4	2	0.73	30	-80	4	1.00	1.00	0.71	0.64	2.58	2.57	0.28	0.27
5	2	0.80	20	-80	5	1.00	1.00	0.66	0.67	2.50	2.67	0.29	0.27
6	2	0.83	4	-20	3	1.00	1.00	0.73	0.82	2.45	2.50	0.24	0.18
7	2	0.94	6	-90	5	1.00	1.00	0.86	0.87	2.34	2.38	0.13	0.11
8	2	0.95	1	-20	5	1.00	1.00	0.86	0.91	2.48	2.31	0.12	0.08
9	2	0.96	4	-90	3	1.00	1.00	0.87	0.90	2.36	2.34	0.14	0.08
10	3	0.10	70	-8	4	0.75	0.77	0.42	0.48	1.22	1.11	0.29	0.25
11	3	0.90	9	-80	4	0.75	0.77	0.80	0.73	-0.33	0.29	0.18	0.25
12	3	0.91	7	-70	6	0.75	0.77	0.76	0.83	0.10	-0.41	0.19	0.12
13	4	0.06	60	-4	2	0.50	0.50	0.42	0.41	0.52	0.84	0.22	0.15
14	4	0.20	40	-10	4	0.50	0.50	0.48	0.46	-0.34	0.04	0.31	0.31
15	4	0.31	20	-9	4	0.50	0.50	0.49	0.44	-0.07	0.30	0.34	0.38
16	4	0.60	4	-6	2	0.50	0.50	0.56	0.58	-0.27	-0.26	0.22	0.26
17	4	0.60	40	-60	3	0.50	0.50	0.58	0.55	-0.96	-0.20	0.28	0.25
18	4	0.73	3	-8	2	0.50	0.50	0.57	0.55	-0.29	0.09	0.24	0.20
19	4	0.80	20	-80	2	0.50	0.50	0.64	0.63	-1.30	-1.21	0.28	0.27
20	4	0.90	1	-9	6	0.50	0.50	0.53	0.48	0.12	0.63	0.21	0.16
21	4	0.96	3	-70	3	0.50	0.50	0.65	0.62	-0.84	-0.38	0.23	0.18
22	5	0.02	80	-2	3	0.25	0.33	0.36	0.31	0.24	0.64	0.17	0.17
23	5	0.07	90	-7	3	0.25	0.33	0.39	0.24	-0.81	0.34	0.19	0.13
24	5	0.53	80	-90	5	0.25	0.33	0.65	0.58	-3.41	-2.44	0.27	0.36
25	5	0.80	1	-4	2	0.25	0.33	0.45	0.42	-0.31	0.11	0.20	0.18
26	5	0.88	4	-30	3	0.25	0.33	0.52	0.49	-0.95	-0.57	0.22	0.21
27	5	0.93	5	-70	4	0.25	0.33	0.57	0.57	-1.63	-1.43	0.27	0.20
28	6	0.10	90	-10	5	0.25	0.22	0.26	0.27	-0.13	0.07	0.22	0.19
29	6	0.19	30	-7	3	0.25	0.22	0.39	0.32	-1.35	-0.45	0.27	0.26
30	6	0.29	50	-20	3	0.25	0.22	0.47	0.48	-2.74	-2.43	0.38	0.36
31	6	0.46	7	-6	6	0.25	0.22	0.38	0.34	-0.90	-0.38	0.23	0.24
32	6	0.57	6	-8	4	0.25	0.22	0.44	0.39	-1.56	-0.59	0.26	0.27
33	6	0.82	20	-90	3	0.25	0.22	0.63	0.55	-5.33	-3.14	0.26	0.21
34	6	0.88	8	-60	4	0.25	0.22	0.57	0.50	-3.30	-1.96	0.16	0.19
35	7	0.06	90	-6	4	0.25	0.14	0.31	0.35	-1.40	-1.43	0.29	0.21
36	7	0.21	30	-8	3	0.25	0.14	0.39	0.31	-2.20	-1.04	0.30	0.23
37	7	0.50	80	-80	5	0.25	0.14	0.51	0.55	-4.18	-4.78	0.34	0.32
38	7	0.69	9	-20	5	0.25	0.14	0.46	0.34	-2.62	-0.88	0.25	0.23
39	7	0.81	7	-30	2	0.25	0.14	0.41	0.34	-2.25	-0.93	0.22	0.21
40	7	0.91	1	-10	2	0.25	0.14	0.34	0.27	-0.71	-0.30	0.19	0.17
Means						0.51	0.51	0.56	0.54	-0.39	0.04	0.23	0.21
Estimated error variance								.0016	.0015	.1370	.1188	.0012	.0015

Table 2. The 40 market entry games that were studied in the estimation experiment. At each trial, each of 4 players has to decide (individually) between “entering a risky market”, or “staying out” (a safer prospect). The payoffs depended on a realization of a binary gamble (the realization at trial t is denoted G_t, and yields “H with probability Ph; and L otherwise”), the number of entrants (E), and two additional parameters (k and S). The exact payoff for player i at trial t is: ${{\displaystyle V}}_i(t)=\left\{{}_{{\text{round(G}}_{\text{t}}\text{/S) with p=}{\text{.5; -round(G}}_{\text{t}}\text{/S) otherwise if i does not enter}}^{{\text{ 10-k(E)+G}}_{\text{t}}\text{ if i enters}}\right\}$ The left hand-columns present the exact value of the different parameters in the 40 games, the right hand columns present the equilibrium predictions, and the main experimental results in the first and second block (B1 and B2).

								Experimental results
The games						Entry at eq.		Entry rates		Efficiency		Alternations
#	K	ph	H	L	S	pure	symmetric	B1	B2	B1	B2	B1	B2
1	2	0.04	70	-3	5	1.00	1.00	0.71	0.80	2.77	2.66	0.16	0.16
2	2	0.23	30	-9	4	1.00	1.00	0.55	0.62	2.64	2.75	0.25	0.23
3	2	0.67	1	-2	3	1.00	1.00	0.88	0.94	2.39	2.24	0.10	0.04
4	2	0.73	30	-80	4	1.00	1.00	0.71	0.64	2.58	2.57	0.28	0.27
5	2	0.80	20	-80	5	1.00	1.00	0.66	0.67	2.50	2.67	0.29	0.27
6	2	0.83	4	-20	3	1.00	1.00	0.73	0.82	2.45	2.50	0.24	0.18
7	2	0.94	6	-90	5	1.00	1.00	0.86	0.87	2.34	2.38	0.13	0.11
8	2	0.95	1	-20	5	1.00	1.00	0.86	0.91	2.48	2.31	0.12	0.08
9	2	0.96	4	-90	3	1.00	1.00	0.87	0.90	2.36	2.34	0.14	0.08
10	3	0.10	70	-8	4	0.75	0.77	0.42	0.48	1.22	1.11	0.29	0.25
11	3	0.90	9	-80	4	0.75	0.77	0.80	0.73	-0.33	0.29	0.18	0.25
12	3	0.91	7	-70	6	0.75	0.77	0.76	0.83	0.10	-0.41	0.19	0.12
13	4	0.06	60	-4	2	0.50	0.50	0.42	0.41	0.52	0.84	0.22	0.15
14	4	0.20	40	-10	4	0.50	0.50	0.48	0.46	-0.34	0.04	0.31	0.31
15	4	0.31	20	-9	4	0.50	0.50	0.49	0.44	-0.07	0.30	0.34	0.38
16	4	0.60	4	-6	2	0.50	0.50	0.56	0.58	-0.27	-0.26	0.22	0.26
17	4	0.60	40	-60	3	0.50	0.50	0.58	0.55	-0.96	-0.20	0.28	0.25
18	4	0.73	3	-8	2	0.50	0.50	0.57	0.55	-0.29	0.09	0.24	0.20
19	4	0.80	20	-80	2	0.50	0.50	0.64	0.63	-1.30	-1.21	0.28	0.27
20	4	0.90	1	-9	6	0.50	0.50	0.53	0.48	0.12	0.63	0.21	0.16
21	4	0.96	3	-70	3	0.50	0.50	0.65	0.62	-0.84	-0.38	0.23	0.18
22	5	0.02	80	-2	3	0.25	0.33	0.36	0.31	0.24	0.64	0.17	0.17
23	5	0.07	90	-7	3	0.25	0.33	0.39	0.24	-0.81	0.34	0.19	0.13
24	5	0.53	80	-90	5	0.25	0.33	0.65	0.58	-3.41	-2.44	0.27	0.36
25	5	0.80	1	-4	2	0.25	0.33	0.45	0.42	-0.31	0.11	0.20	0.18
26	5	0.88	4	-30	3	0.25	0.33	0.52	0.49	-0.95	-0.57	0.22	0.21
27	5	0.93	5	-70	4	0.25	0.33	0.57	0.57	-1.63	-1.43	0.27	0.20
28	6	0.10	90	-10	5	0.25	0.22	0.26	0.27	-0.13	0.07	0.22	0.19
29	6	0.19	30	-7	3	0.25	0.22	0.39	0.32	-1.35	-0.45	0.27	0.26
30	6	0.29	50	-20	3	0.25	0.22	0.47	0.48	-2.74	-2.43	0.38	0.36
31	6	0.46	7	-6	6	0.25	0.22	0.38	0.34	-0.90	-0.38	0.23	0.24
32	6	0.57	6	-8	4	0.25	0.22	0.44	0.39	-1.56	-0.59	0.26	0.27
33	6	0.82	20	-90	3	0.25	0.22	0.63	0.55	-5.33	-3.14	0.26	0.21
34	6	0.88	8	-60	4	0.25	0.22	0.57	0.50	-3.30	-1.96	0.16	0.19
35	7	0.06	90	-6	4	0.25	0.14	0.31	0.35	-1.40	-1.43	0.29	0.21
36	7	0.21	30	-8	3	0.25	0.14	0.39	0.31	-2.20	-1.04	0.30	0.23
37	7	0.50	80	-80	5	0.25	0.14	0.51	0.55	-4.18	-4.78	0.34	0.32
38	7	0.69	9	-20	5	0.25	0.14	0.46	0.34	-2.62	-0.88	0.25	0.23
39	7	0.81	7	-30	2	0.25	0.14	0.41	0.34	-2.25	-0.93	0.22	0.21
40	7	0.91	1	-10	2	0.25	0.14	0.34	0.27	-0.71	-0.30	0.19	0.17
Means						0.51	0.51	0.56	0.54	-0.39	0.04	0.23	0.21
Estimated error variance								.0016	.0015	.1370	.1188	.0012	.0015

Figure 1. Proportion of alternation as a function of Ph. Each data point summarizes the results of one game. The outlier (alternation rate of 0.07 when Ph = 0.67) is Problem 3: The problem with the lowest payoff variance, and the only problem in which entry cannot lead to losses.

Figure 1. Proportion of alternation as a function of Ph. Each data point summarizes the results of one game. The outlier (alternation rate of 0.07 when Ph = 0.67) is Problem 3: The problem with the lowest payoff variance, and the only problem in which entry cannot lead to losses.

Table 3. Summary of correlation analyses that examine the possibility of consistent individual differences. The summary scores are based on 180 correlation analyses (180 pairs of games) for each of the four variables.

Variable	Mean correlation	Proportion of positive correlations
Entry rate	0.249	0.844
Maximization	0.058	0.611
Alternation	0.415	0.983
Recency	0.281	0.888

Table 3. Summary of correlation analyses that examine the possibility of consistent individual differences. The summary scores are based on 180 correlation analyses (180 pairs of games) for each of the four variables.

Variable	Mean correlation	Proportion of positive correlations
Entry rate	0.249	0.844
Maximization	0.058	0.611
Alternation	0.415	0.983
Recency	0.281	0.888

Table 4. The baseline models, the estimated parameters, and the implied normalized MSD scores by statistic and block.

Model	Fitted parameters	Normalized Mean Squared Deviation Scores by statistic and block
		Entry rates		Efficiency		Alteration		Mean
	Block:	1	2	1	2	1	2
Pure		26.52	21.56	39.41	28.01	49.50	35.26	33.38
Symmetric		29.57	25.11	21.13	13.24	30.59	25.95	24.26
RL	λ = 4, w = 0.01	8.57	16.37	5.19	8.84	19.14	12.22	11.72
NRL	λ = 12, w = 0.025	6.36	14.03	3.59	7.35	4.58	1.53	6.24
SFP	λ = 1.5, w = 0.1	5.91	5.36	9.37	14.99	6.53	3.79	7.66
NFP	λ = 4, w = 0.15	4.75	4.16	3.60	6.13	2.70	3.80	4.19
EWA	λ = 0.7, φ = 0.8, δ = 0.5, ρ = 0.4	10.06	8.91	4.69	9.22	4.38	2.49	6.62
SAW	εi ~ U[0,0.02], wi ~ U[0,1], ρi ~ U[0,0.02], and µi = {1, 2, or 3}.	3.93	2.49	1.87	2.04	4.18	5.37	3.31
I-SAW	εi ~ U[0,0.24], wi ~ U[0,0.8], ρi ~ U[0,0.2], πi ~ U[0,0.6], and µi = {1, 2, or 3}.	1.56	1.19	1.37	1.47	1.43	1.30	1.38

Table 4. The baseline models, the estimated parameters, and the implied normalized MSD scores by statistic and block.

Model	Fitted parameters	Normalized Mean Squared Deviation Scores by statistic and block
		Entry rates		Efficiency		Alteration		Mean
	Block:	1	2	1	2	1	2
Pure		26.52	21.56	39.41	28.01	49.50	35.26	33.38
Symmetric		29.57	25.11	21.13	13.24	30.59	25.95	24.26
RL	λ = 4, w = 0.01	8.57	16.37	5.19	8.84	19.14	12.22	11.72
NRL	λ = 12, w = 0.025	6.36	14.03	3.59	7.35	4.58	1.53	6.24
SFP	λ = 1.5, w = 0.1	5.91	5.36	9.37	14.99	6.53	3.79	7.66
NFP	λ = 4, w = 0.15	4.75	4.16	3.60	6.13	2.70	3.80	4.19
EWA	λ = 0.7, φ = 0.8, δ = 0.5, ρ = 0.4	10.06	8.91	4.69	9.22	4.38	2.49	6.62
SAW	εi ~ U[0,0.02], wi ~ U[0,1], ρi ~ U[0,0.02], and µi = {1, 2, or 3}.	3.93	2.49	1.87	2.04	4.18	5.37	3.31
I-SAW	εi ~ U[0,0.24], wi ~ U[0,0.8], ρi ~ U[0,0.2], πi ~ U[0,0.6], and µi = {1, 2, or 3}.	1.56	1.19	1.37	1.47	1.43	1.30	1.38

Table 5. The predictions of the best baseline models (I-SAW): The lowest row presents the correlation with the experimental results by statistic.

The games						Entry rates		Efficiency		Alternations
#	K	Ph	h	l	Sf	B1	B2	B1	B2	B1	B2
1	2	0.04	70	-3	5	0.78	0.81	2.60	2.56	0.17	0.13
2	2	0.23	30	-9	4	0.58	0.62	2.39	2.62	0.24	0.22
3	2	0.67	1	-2	3	0.90	0.91	2.33	2.32	0.10	0.08
4	2	0.73	30	-80	4	0.64	0.64	2.47	2.59	0.26	0.25
5	2	0.80	20	-80	5	0.67	0.67	2.47	2.61	0.24	0.23
6	2	0.83	4	-20	3	0.77	0.78	2.49	2.57	0.20	0.18
7	2	0.94	6	-90	5	0.82	0.82	2.39	2.49	0.15	0.14
8	2	0.95	1	-20	5	0.84	0.85	2.42	2.47	0.13	0.11
9	2	0.96	4	-90	3	0.84	0.86	2.35	2.43	0.13	0.11
10	3	0.10	70	-8	4	0.42	0.45	0.97	1.23	0.23	0.21
11	3	0.90	9	-80	4	0.74	0.75	-0.06	0.11	0.19	0.18
12	3	0.91	7	-70	6	0.76	0.76	-0.15	0.05	0.18	0.17
13	4	0.06	60	-4	2	0.41	0.43	0.22	0.34	0.24	0.22
14	4	0.20	40	-10	4	0.43	0.44	-0.04	0.25	0.27	0.25
15	4	0.31	20	-9	4	0.48	0.49	-0.22	0.01	0.29	0.28
16	4	0.60	4	-6	2	0.52	0.52	-0.20	-0.05	0.30	0.28
17	4	0.60	40	-60	3	0.55	0.55	-0.78	-0.47	0.29	0.28
18	4	0.73	3	-8	2	0.53	0.52	-0.20	-0.08	0.29	0.27
19	4	0.80	20	-80	2	0.65	0.64	-1.65	-1.23	0.24	0.24
20	4	0.90	1	-9	6	0.52	0.52	0.07	0.06	0.25	0.23
21	4	0.96	3	-70	3	0.61	0.59	-0.80	-0.51	0.21	0.19
22	5	0.02	80	-2	3	0.35	0.35	-0.08	0.06	0.23	0.20
23	5	0.07	90	-7	3	0.31	0.32	-0.42	-0.05	0.21	0.19
24	5	0.53	80	-90	5	0.52	0.52	-2.03	-1.59	0.29	0.28
25	5	0.80	1	-4	2	0.40	0.40	-0.24	-0.10	0.25	0.23
26	5	0.88	4	-30	3	0.47	0.46	-0.89	-0.73	0.25	0.22
27	5	0.93	5	-70	4	0.51	0.50	-1.43	-1.08	0.24	0.21
28	6	0.10	90	-10	5	0.31	0.31	-1.08	-0.63	0.22	0.20
29	6	0.19	30	-7	3	0.36	0.36	-1.28	-0.90	0.26	0.24
30	6	0.29	50	-20	3	0.42	0.42	-2.05	-1.62	0.29	0.27
31	6	0.46	7	-6	6	0.35	0.35	-0.86	-0.67	0.27	0.24
32	6	0.57	6	-8	4	0.36	0.35	-0.94	-0.70	0.27	0.25
33	6	0.82	20	-90	3	0.60	0.57	-4.69	-3.73	0.25	0.24
34	6	0.88	8	-60	4	0.47	0.46	-2.20	-1.83	0.25	0.22
35	7	0.06	90	-6	4	0.26	0.26	-1.19	-0.68	0.20	0.18
36	7	0.21	30	-8	3	0.34	0.33	-1.77	-1.32	0.26	0.24
37	7	0.50	80	-80	5	0.49	0.48	-4.31	-3.61	0.29	0.28
38	7	0.69	9	-20	5	0.37	0.36	-1.84	-1.52	0.26	0.24
39	7	0.81	7	-30	2	0.37	0.36	-1.81	-1.50	0.26	0.23
40	7	0.91	1	-10	2	0.29	0.28	-0.76	-0.58	0.22	0.19
Means						0.525	0.526	-0.270	-0.011	0.234	0.215
Correlation with the experimental results						0.973	0.979	0.982	0.970	0.750	0.834

Table 5. The predictions of the best baseline models (I-SAW): The lowest row presents the correlation with the experimental results by statistic.

The games						Entry rates		Efficiency		Alternations
#	K	Ph	h	l	Sf	B1	B2	B1	B2	B1	B2
1	2	0.04	70	-3	5	0.78	0.81	2.60	2.56	0.17	0.13
2	2	0.23	30	-9	4	0.58	0.62	2.39	2.62	0.24	0.22
3	2	0.67	1	-2	3	0.90	0.91	2.33	2.32	0.10	0.08
4	2	0.73	30	-80	4	0.64	0.64	2.47	2.59	0.26	0.25
5	2	0.80	20	-80	5	0.67	0.67	2.47	2.61	0.24	0.23
6	2	0.83	4	-20	3	0.77	0.78	2.49	2.57	0.20	0.18
7	2	0.94	6	-90	5	0.82	0.82	2.39	2.49	0.15	0.14
8	2	0.95	1	-20	5	0.84	0.85	2.42	2.47	0.13	0.11
9	2	0.96	4	-90	3	0.84	0.86	2.35	2.43	0.13	0.11
10	3	0.10	70	-8	4	0.42	0.45	0.97	1.23	0.23	0.21
11	3	0.90	9	-80	4	0.74	0.75	-0.06	0.11	0.19	0.18
12	3	0.91	7	-70	6	0.76	0.76	-0.15	0.05	0.18	0.17
13	4	0.06	60	-4	2	0.41	0.43	0.22	0.34	0.24	0.22
14	4	0.20	40	-10	4	0.43	0.44	-0.04	0.25	0.27	0.25
15	4	0.31	20	-9	4	0.48	0.49	-0.22	0.01	0.29	0.28
16	4	0.60	4	-6	2	0.52	0.52	-0.20	-0.05	0.30	0.28
17	4	0.60	40	-60	3	0.55	0.55	-0.78	-0.47	0.29	0.28
18	4	0.73	3	-8	2	0.53	0.52	-0.20	-0.08	0.29	0.27
19	4	0.80	20	-80	2	0.65	0.64	-1.65	-1.23	0.24	0.24
20	4	0.90	1	-9	6	0.52	0.52	0.07	0.06	0.25	0.23
21	4	0.96	3	-70	3	0.61	0.59	-0.80	-0.51	0.21	0.19
22	5	0.02	80	-2	3	0.35	0.35	-0.08	0.06	0.23	0.20
23	5	0.07	90	-7	3	0.31	0.32	-0.42	-0.05	0.21	0.19
24	5	0.53	80	-90	5	0.52	0.52	-2.03	-1.59	0.29	0.28
25	5	0.80	1	-4	2	0.40	0.40	-0.24	-0.10	0.25	0.23
26	5	0.88	4	-30	3	0.47	0.46	-0.89	-0.73	0.25	0.22
27	5	0.93	5	-70	4	0.51	0.50	-1.43	-1.08	0.24	0.21
28	6	0.10	90	-10	5	0.31	0.31	-1.08	-0.63	0.22	0.20
29	6	0.19	30	-7	3	0.36	0.36	-1.28	-0.90	0.26	0.24
30	6	0.29	50	-20	3	0.42	0.42	-2.05	-1.62	0.29	0.27
31	6	0.46	7	-6	6	0.35	0.35	-0.86	-0.67	0.27	0.24
32	6	0.57	6	-8	4	0.36	0.35	-0.94	-0.70	0.27	0.25
33	6	0.82	20	-90	3	0.60	0.57	-4.69	-3.73	0.25	0.24
34	6	0.88	8	-60	4	0.47	0.46	-2.20	-1.83	0.25	0.22
35	7	0.06	90	-6	4	0.26	0.26	-1.19	-0.68	0.20	0.18
36	7	0.21	30	-8	3	0.34	0.33	-1.77	-1.32	0.26	0.24
37	7	0.50	80	-80	5	0.49	0.48	-4.31	-3.61	0.29	0.28
38	7	0.69	9	-20	5	0.37	0.36	-1.84	-1.52	0.26	0.24
39	7	0.81	7	-30	2	0.37	0.36	-1.81	-1.50	0.26	0.23
40	7	0.91	1	-10	2	0.29	0.28	-0.76	-0.58	0.22	0.19
Means						0.525	0.526	-0.270	-0.011	0.234	0.215
Correlation with the experimental results						0.973	0.979	0.982	0.970	0.750	0.834