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. Author manuscript; available in PMC: 2022 Feb 24.
Published in final edited form as: Proc ACM Symp User Interface Softw Tech. 2021 Oct 12;2021:1122–1143. doi: 10.1145/3472749.3474811

Table 8:

Fitting results for 31 distributing models on Zhou and Ren’s straight tunnel dataset. As explained in Section 4, we use Steering law (Equation 1) to predict the mean (or location) parameter, and one of the six variance models (Table 1) to predict the variance (or scale) parameter, as explained in Table 2. a and b are parameters of Steering law, and c, d and e are parameters of variance models. Parameter estimations are shown in mean and 95% credible interval of posterior distributions. Fitness results are reported in AIC and WAIC metrics. As shown, the quadratic variance model (Model #4 in Table 1) has the best (or second-best) fitting results across all distribution types, measured by AIC, and WAIC.

Model Model Parameters (Mean and 95% Credible Interval) Information Criteria
Variance Model Distribution Type a b c d e k AIC WAIC
#1. σ2 = c Gaussian 0.529 [0.467, 0.59] 0.029 [0.026, 0.031] 0.24 [0.218, 0.265] N/A N/A N/A 12336.8 12335.9
Truncated Gaussian 0.402 [0.31, 0.485] 0.032 [0.029, 0.035] 0.293 [0.258, 0.334] N/A N/A N/A 12271.1 12270.3
Lognormal 0.704 [0.652, 0.756] 0.021 [0.019, 0.023] 0.319 [0.276, 0.37] N/A N/A N/A 12186.8 12184.9
Gamma 0.681 [0.628, 0.734] 0.022 [0.02, 0.024] 0.25 [0.223, 0.28] N/A N/A N/A 12203.4 12201.5
Extreme value 0.721 [0.669, 0.773] 0.019 [0.017, 0.021] 0.262 [0.235, 0.292] N/A N/A N/A 12248.0 12246.7
#2. σ2 = (c · ID)2 Gaussian 0.469 [0.417, 0.522] 0.033 [0.028, 0.037] 0.033 [0.031, 0.035] N/A N/A N/A 12439.5 12437.5
Truncated Gaussian 0.564 [0.496, 0.639] 0.02 [0.013, 0.027] 0.037 [0.035, 0.04] N/A N/A N/A 12357.4 12355.1
Lognormal 0.32 [0.279, 0.359] 0.045 [0.042, 0.049] 0.036 [0.034, 0.039] N/A N/A N/A 12203.0 12200.1
Gamma 0.324 [0.281, 0.366] 0.045 [0.042, 0.049] 0.033 [0.031, 0.035] N/A N/A N/A 12246.4 12243.5
Extreme value 0.292 [0.252, 0.329] 0.046 [0.042, 0.049] 0.032 [0.03, 0.033] N/A N/A N/A 12262.0 12259.1
#3. σ2 = c + d · ID Gaussian 0.519 [0.465, 0.573] 0.029 [0.026, 0.032] 0.046 [0.009, 0.084] 0.01 [0.008, 0.013] N/A N/A 12245.1 12242.2
Truncated Gaussian 0.489 [0.426, 0.547] 0.029 [0.026, 0.033] 0.067 [0.017, 0.12] 0.011 [0.007, 0.014] N/A N/A 12218.0 12215.3
Lognormal 0.527 [0.466, 0.59] 0.029 [0.026, 0.033] 0.046 [−0.01, 0.104] 0.013 [0.009, 0.018] N/A N/A 12131.4 12127.4
Gamma 0.522 [0.468, 0.58] 0.029 [0.026, 0.032] 0.038 [0.0001, 0.052] 0.011 [0.008, 0.014] N/A N/A 12119.7 12115.6
Extreme value 0.511 [0.456, 0.567] 0.03 [0.026, 0.033] 0.023 [−0.012, 0.061] 0.012 [0.01, 0.015] N/A N/A 12131.4 12124.6
#4. σ2 = c + d · ID2 Gaussian 0.531 [0.473, 0.587] 0.029 [0.026, 0.032] 0.133 [0.111, 0.158] 0.0002 [0.0001, 0.0003] N/A N/A 12252.0 12249.2
Truncated Gaussian 0.492 [0.424, 0.557] 0.029 [0.026, 0.033] 0.162 [0.13, 0.201] 0.0002 [0.0001, 0.0003] N/A N/A 12223.2 12220.7
Lognormal 0.526 [0.465, 0.589] 0.029 [0.026, 0.033] 0.14 [0.102, 0.182] 0.324 [0.211, 0.462] N/A N/A 12128.4 12124.3
Gamma 0.533 [0.475, 0.587] 0.029 [0.025, 0.032] 0.12 [0.097, 0.146] 0.0002 [0.0002, 0.0003] N/A N/A 12120.5 12116.2
Extreme value 0.512 [0.452, 0.569] 0.03 [0.026, 0.033] 0.111 [0.088, 0.137] 0.0003 [0.0002, 0.0004] N/A N/A 12129.4 12124.9
exGaussian 0.44 [0.377, 0.5] 0.035 [0.031, 0.04] 0.06 [0.037, 0.086] 0.00006 [0.00004, 0.00008] N/A 0.04 [0.04, 0.05] 12193.7 12194.7
#5. σ2 = (c + d · ID)2 Gaussian 0.524 [0.47, 0.582] 0.029 [0.026, 0.032] 0.291 [0.252, 0.332] 0.01 [0.007, 0.012] N/A N/A 12247.1 12244.3
Truncated Gaussian 0.491 [0.427, 0.553] 0.029 [0.026, 0.033] 0.325 [0.274, 0.379] 0.009 [0.007, 0.012] N/A N/A 12219.6 12216.9
Lognormal 0.52 [0.458, 0.579] 0.03 [0.026, 0.033] 0.286 [0.222, 0.348] 0.013 [0.009, 0.017] N/A N/A 12128.5 12124.4
Gamma 0.523 [0.471, 0.579] 0.029 [0.026, 0.032] 0.269 [0.224, 0.315] 0.011 [0.008, 0.014] N/A N/A 12118.5 12114.3
Extreme value 0.508 [0.456, 0.564] 0.03 [0.027, 0.033] 0.252 [0.212, 0.298] 0.012 [0.01, 0.015] N/A N/A 12127.9 12123.8
#6. σ2 = c + d · ID + e · ID2 Gaussian 0.522 [0.465, 0.578] 0.029 [0.026, 0.032] 0.069 [0.023, 0.134] 0.007 [0.0001, 0.01] 0.00007 [0.000002, 0.0002] N/A 12248.5 12243.8
Truncated Gaussian 0.49 [0.424, 0.553] 0.029 [0.026, 0.033] 0.099 [0.031, 0.188] 0.007 [−0.002, 0.013] 0.00008 [0.000003, 0.0003] N/A 12221.9 12217.8
Lognormal 0.525 [0.462, 0.588] 0.03 [0.026, 0.033] 0.123 [0.028, 0.228] 0.002 [−0.01, 0.014] 0.0003 [0.000009, 0.0006] N/A 12131.2 12126.1
Gamma 0.525 [0.469, 0.581] 0.029 [0.026, 0.032] 0.082 [0.022, 0.156] 0.005 [−0.004, 0.011] 0.0001 [0.00001, 0.0003] N/A 12121.5 12116.1
Extreme value 0.509 [0.453, 0.565] 0.03 [0.027, 0.033] 0.077 [0.013,0.151] 0.005 [−0.005, 0.013] 0.0002 [0.000002, 0.0004] N/A 12131.1 12125.4