Table 6. Models used to fit LmrP data... | Rockefeller University Press

Table 6.

Models used to fit LmrP data (Fig. 8)

Model	n	Linked	q	SSR	$χ_{υ}^{2}$	BIC_WLS	ΔBIC_WLS	pK
1	2	Nothing	64	0.075598	1.1230	−30,382.8	139.7	—
2	3	Nothing	88	0.074582	1.1129	−30,242.2	280.4	—
3	2	Gaussians	36	0.079455	1.1651	−30,474.8	47.7	4.6 ± 0.6
4	3	Gaussians	46	0.077139	1.1329	−30,483.0	39.6	—
5	3	Custom	39	0.078279	1.1463	−30,498.7	23.8	4.6 ± 0.7
6	3	Custom	39	0.078139	1.1419	−30,509.5	13.1	4.8 ± 1.0
7	3	Custom	39	0.077450	1.1365	−30,522.6	0.0	4.7 ± 1.3

Model	n	Linked	q	SSR	$χ_{υ}^{2}$	BIC_WLS	ΔBIC_WLS	pK
1	2	Nothing	64	0.075598	1.1230	−30,382.8	139.7	—
2	3	Nothing	88	0.074582	1.1129	−30,242.2	280.4	—
3	2	Gaussians	36	0.079455	1.1651	−30,474.8	47.7	4.6 ± 0.6
4	3	Gaussians	46	0.077139	1.1329	−30,483.0	39.6	—
5	3	Custom	39	0.078279	1.1463	−30,498.7	23.8	4.6 ± 0.7
6	3	Custom	39	0.078139	1.1419	−30,509.5	13.1	4.8 ± 1.0
7	3	Custom	39	0.077450	1.1365	−30,522.6	0.0	4.7 ± 1.3

The models differ in the number of Gaussian components, n, used to define the distance distributions and in how their parameters are linked for the different datasets. In all models, the modulation depths, Δ, and the background parameters, η, for the different datasets are not linked. pK values are the negative logarithms of the dissociation constants.

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