An Algorithm for Optimally Fitting a Wiener Model

Table 3

Training and validation statistics for Wiener networks fit to model blood glucose concentrations for four diabetic subjects. Note that PM is the proposed methodology, GN is the Gauss-Newton algorithm, and LM is the Levenberg-Marquardt algorithm.

Subject	Algorithm	AAETr(mg/dL)	𝑟fit	𝑟Val	Time (s)
1	PM	12.4	0.60	0.59	4127
	GN	12.4	0.30	0.53	1.26
	LM	12.5	0.35	0.54	3.36
2	PM	6.8	0.84	0.56	10592
	GN	11.1	0.51	0.23	3.08
	LM	12.8	0.25	0.33	4.66
3	PM	11.5	0.71	0.52	4735
	GN	10.0	0.54	0.37	2.64
	LM	11.2	0.51	0.39	4.09
	PM	11.4	0.82	0.68	7032
4	GN	18.7	0.28	0.39	1.57
	LM	14.7	0.69	0.37	3.68