Research Article

Separable Nonlinear Least-Squares Parameter Estimation for Complex Dynamic Systems

Table 2

MSE ratios for linear parameters (large samples).

PriorLow noiseHigh noise
SIRLVGMAFHNSIRLVGMAFHN

Low12.09.63.93.93.83.22.22.2
Medium4.14.32.81.91.61.61.61.3
High1.02.20.72.30.71.20.51.5

The sample size is for the GMA and Lotka–Volterra models; for the FitzHugh–Nagumo system; and for the SIR model. The noise levels are and . For an interpretation of the results, see Table 1. There is an increased advantage of SLS over NLS in comparison to Table 1.