Ranking with respect to the reference

Excellent	Good	Fair	Poor
	SIVdata (1)   asano (2)   gallovic001 (6)   gallovic01 (7)   gallovic1 (8)   ids (10)	cedrict (3)   cedrict3 (5)   hoby (9)	cedrict2 (4)

Dissimilarity matrix

Solution	SIVdata	asano	cedrict	cedrict2	cedrict3	gallovic001	gallovic01	gallovic1	hoby	ids
SIVdata	0.00	6.91	49.27	83.74	33.11	11.18	9.62	9.15	18.03	27.40
asano	6.91	0.00	44.80	84.26	31.77	7.00	6.04	5.44	20.93	16.61
cedrict	49.27	44.80	0.00	24.12	29.06	44.15	37.85	38.90	65.77	38.58
cedrict2	83.74	84.26	24.12	0.00	66.10	81.77	74.60	76.82	95.36	80.77
cedrict3	33.11	31.77	29.06	66.10	0.00	30.62	30.67	29.98	54.03	24.72
gallovic001	11.18	7.00	44.15	81.77	30.62	0.00	4.58	2.99	17.26	14.35
gallovic01	9.62	6.04	37.85	74.60	30.67	4.58	0.00	0.46	18.25	16.29
gallovic1	9.15	5.44	38.90	76.82	29.98	2.99	0.46	0.00	17.19	14.20
hoby	18.03	20.93	65.77	95.36	54.03	17.26	18.25	17.19	0.00	38.10
ids	27.40	16.61	38.58	80.77	24.72	14.35	16.29	14.20	38.10	0.00

Each element represents a measure of dissimilarity between pairs of models obtained using normalized square metric

Note
This analysis employs multidimensional scaling (Borg and Groenen, 2005) to compare the slip models. The dissimilarities are obtained for all pairs of slip models, viz. dissimilarity matrix and embedded in low dimensional Euclidean space. We define four categories or levels of similarity: ”excellent”, ”good”, ”fair”, and ”poor” with respect to a reference (or target) solution or a centroid measure in absence of a reference solution.

Graphical interpretation for the similarity scale is as follows:

Excellent	Solution/s located inside the innermost circle
Good	Solution/s located between the innermost and middle circle
Fair	Solution/s located between the middle and outermost circle
Poor	Solutions/s located outside the outermost circle

For more details on the technique:

1.	Borg, I. and P. Groenen (2005). Modern Multidimensional Scaling, 2nd edition. New York, Springer
2.	Razafindrakoto, H. N., Mai, P. M., Genton, M. G., Zhang, L., and Thingbaijam, K. K. (2015). Quantifying variability in earthquake rupture models using multidimensional scaling: application to the 2011 Tohoku earthquake. Geophysical Journal International, 202(1), 17-40.