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Table 1
Simulated datasets with known density distributions.
| Dataset | Component | Points | Distribution | |
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| 1 | Trivariate Gaussian 1 | 40 000 | M1 = (50,50,50) | CM1 = diag(30) |
| Uniform random noise | 20 000 | Uniform(x,y,z) = [0,100] | ||
| 2 | Trivariate Gaussian 1 | 20 000 | M1 = (25,25,25) | CM1 = diag(5) |
| Trivariate Gaussian 2 | 20 000 | M2 = (65,65,65) | CM2 = diag(20) | |
| Uniform random noise | 20 000 | Uniform(x,y,z) = [0,100] | ||
| 3 | Trivariate Gaussian 1 | 20 000 | M1 = (24,10,10) | CM1 = diag(2) |
| Trivariate Gaussian 2 | 20 000 | M2 = (33,70,40) | CM2 = diag(10) | |
| Trivariate Gaussian 3 | 20 000 | M3 = (90,20,80) | CM3 = diag(1) | |
| Trivariate Gaussian 4 | 20 000 | M4 = (60,80,23) | CM4 = diag(5) | |
| Uniform random noise | 40 000 | Uniform(x,y,z) = [0,100] | ||
| 4 | Wall-like structure | 30 000 | Uniform(x,y) = [0,100] ,Gaussian(z) = [M = 50, var = 5] | |
| Filament-like structure | 30 000 | Uniform(z) = [0,100] ,Gaussian(x,y) = [M = 50, var = 5] | ||
| 5 | Wall-like structure 1 | 20 000 | Uniform(x,z) = [0,100] ,Gaussian(y) = [M = 10, var = 5] | |
| Wall-like structure 2 | 20 000 | Uniform(x,y) = [0,100] ,Gaussian(z) = [M = 50, var = 5] | ||
| Wall-like structure 3 | 20 000 | Uniform(x,z) = [0,100] ,Gaussian(y) = [M = 50, var = 5] | ||
| 6 | Log-normal | 60 000 | Log − normal(x,y,z) = [M = 3, var = 4] | |
Notes. M = mean, CM = covariance matrix.
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