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The principle of maximum entropy is applied to the spectral analysis of adata signal with general variance matrix and containing gaps in the record. Therole of the entropic regularizer is to prevent one from overestimatingstructure in the spectrum when faced with imperfect data. Several arguments arepresented suggesting that the arbitrary prefactor should not be introduced tothe entropy term. The introduction of that factor is not required when acontinuous Poisson distribution is used for the amplitude coefficients. Wecompare the formalism for when the variance of the data is known explicitly tothat for when the variance is known only to lie in some finite range. Theresult of including the entropic measure factor is to suggest a spectrumconsistent with the variance of the data which has less structure than thatgiven by the forward transform. An application of the methodology to exampledata is demonstrated.

MaxEnt power spectrum estimation using the Fourier transform for irregularly sampled data applied to a record of stellar luminosity