The peripheral vascular resistance (RPV) control is known to be largely sympathetically-mediated; thus assessment of the RPV control would allow us to infer valuable information regarding sympathetic nervous activity. The linear and 2nd-order nonlinear minimal models were used to capture the influences of blood pressure (baroreflex) and respiration (respiratory-coupling) on fluctuations of RPV. To validate the minimal models, they were applied on the "data" generated by the simulation model developed in our previous study. This study demonstrated that the linear minimal model was able to recover the "true" (simulated) kernels. The nonlinear model was able to detect the increase in nonlinearity in the system. The system gains derived from the estimated kernels showed strong relationship with the simulation gains, suggesting that the system gains could be employed as potential biomarkers of autonomic function. These results also showed that the nonlinear model had sufficient sensitivity to detect the difference in autonomic reactivity between subjects with mild and severe metabolic syndrome and obstructive sleep apnea syndrome exposed to orthostatic stress.