An approach to assessing closed-loop physiologic regulation by the analysis of multiple fluctuating physiologic signals is presented. In particular, the couplings among heart rate, instantaneous lung volume, and arterial blood pressure have been studied. The procedure used consists of several steps. First, a block diagram model is constructed to display the assumed interrelationships among the measured data. Second, linear, constant-coefficient, autoregressive moving-average equations are written to describe each block in the model. Third, the physiologic signals are recorded under conditions which ensure that their frequency content is broadband (e.g., during random interval breathing). Finally, the set of coefficients that result in an optimum least squares fit to the data is found. These parameters specify the transfer functions that correspond to the blocks in the original model. Preliminary results suggest that the time constants and sensitivities inferred from the estimated transfer functions agree with more invasive direct measurements reported in the literature.