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. 2022 Jan 6;8:e790. doi: 10.7717/peerj-cs.790

Table 2. Dimension estimates on synthetic benchmark datasets.

The table shows true dimension values (d), median-Farahmand-Szepesvári-Audibert (mFSA), corrected median Farahmand-Szepesvári-Audibert (cmFSA), DANCo, Maximum Likelihood (Levina) and 2NN mean estimates from N = 100 realizations. cmFSA and DANCo was applied in integer and in fractal modes. The mean percentage error (MPE) values can be seen in the bottom line, the Matlab version of DANCo estimator (DANCo M) produced the smallest error followed by the cmFSA estimator.

Dataset d mFSA cmFSA frac cmFSA DANCo R DANCo M frac DANCo M Levina 2NN
M 1 10 9.09 11.19 11.08 11.34 10.42 10.30 10.15 9.40
M 2 3 2.87 3.02 3.00 3.00 2.90 3.00 3.20 2.93
M 3 4 3.83 4.14 4.00 5.00 3.84 4.00 4.29 3.87
M 4 4 3.95 4.29 4.00 5.00 3.92 4.00 4.38 3.91
M 5 2 1.97 2.00 2.00 2.00 1.98 2.00 2.19 1.99
M 6 6 6.38 7.38 7.16 9.00 6.72 7.00 7.04 5.93
M 7 2 1.95 1.98 2.00 2.00 1.96 2.00 2.18 1.98
M 9 20 14.58 20.07 20.10 19.16 19.24 19.09 16.38 15.55
M 10a 10 8.21 9.90 10.00 10.00 9.56 9.78 9.20 8.63
M 10b 17 12.76 16.95 16.96 16.04 16.39 16.24 14.33 13.58
M 10c 24 16.80 24.10 24.06 23.61 23.39 23.26 18.89 18.04
M 10d 70 35.64 69.84 69.84 69.73 71.00 70.91 40.35 40.05
M 11 2 1.97 2.00 2.00 2.00 1.97 2.00 2.19 1.98
M 12 20 15.64 21.96 21.98 21.72 20.88 20.00 17.72 17.24
M 13 1 1.00 0.96 1.00 1.00 1.00 1.00 1.11 1.00
MPE 13.58 4.73 2.89 9.64 3.39 2.35 13.23 10.91