Abstract
An analogue of the periodogram method for unequally spaced data is presented with a view to resolving the frequency structure of the observations. The algorithm is explicitly based on the sequential least squares procedure. In particular, the key concept is that the with-in-plot spectral analysis can be augmented by the between-plot information to make inferences about common characteristics. It is also shown how the between-plot random variations can be incorporated into the multiple harmonic regression model. A detailed spectral analysis investigates the periodic fluctuations in four cardio-circulatory variables, measured by autorhythmometric observation by eight men at rest and extending over a time span of 2 years. The spectral curves show the existence of circadian and circaseptan rhythmicities. The amplitude modulation of the dian rhythm by circaseptan variation is assimilated with the rhythmicity of work during the week. The blood-pressure variables situate their maximum annual peak in the winter period. These quasi-periodic fluctuations appear to be related to the amount of physical activity performed in time by the subjects.