Fig 1.
Joint fitting problem.
Table 1.
Input matrix a and target margins r, c.
Table 2.
IPF output bIPF.
Fig 2.
Bilinear interpolation.
Table 3.
CBJF output bCBJF.
Fig 3.
Collection view of CBJF (Partition lines are for the example in Table 1).
Fig 4.
Distribution view of CBJF.
Fig 5.
Mapping x(k) to .
Fig 6.
Reference joint types in the test set.
(a) Bivariate normal, (b) Bimodal, (c) Lower tail dependence, (d) U-shape, (e) Circle.
Fig 7.
Target marginal modification operators.
(a) Original marginal distribution, (b) Skew left, (c) Skew right, (d) Uniform, (e) Fat tail, (f) Thin tail, (g) Perturbation.
Fig 8.
Output results for normal joint distribution and fat tail target margins.
Table 4.
Pearson correlation coefficients ρ(X,Y).
Table 5.
Spearman’s rank correlation coefficients s(X,Y).
Table 6.
Kendall’s rank correlation coefficients τ(X,Y).
Table 7.
MIC (Maximal Information Coefficient).
Fig 9.
Results from the normal joint distribution with skew, fat tail and thin tail operators.
Fig 10.
Results from the bimodal joint distribution with skew, fat tail and thin tail operators.
Fig 11.
Results from the tail dependent joint distribution with skew, fat tail and thin tail operators.
Fig 12.
Results from the U-shape joint distribution with skew, fat tail and thin tail operators.
Fig 13.
Results from the circle joint distribution with skew, fat tail and thin tail operators.
Fig 14.
Synthetic population for ED(emergency department) simulation.
Table 8.
Dependency measures for synthetic ED patient populations.