On the detection of Lorentzian profiles in a power spectrum: a Bayesian approach using ignorance priors

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Table 3:

Global fit parameters.
	A₁	A₂	A₃
	B₁	B₂	B₃
Power laws	25743 (6200)	22 (6)	2.2 (0.11)
	252311 (25000)	16477 (1950)	1637 (62)
	P_g	$\nu_{\rm max}$	$\sigma$
Gaussian term	0.500 (0.015)	1657 (28)	538 (26)
White noise	P_n = 0.33 (0.005)

The amplitudes of the power laws (A_i), the height of the Gaussian part (P_g), and the white noise components (P_n) are given in ppm²/ $\mu$ Hz. The power law time scales (B_i) are given in seconds and the center ( $\nu_{\rm max}$ ) and width ( $\sigma$ ) of the Gaussian part are in $\mu$ Hz. One-sigma error estimates are given in brackets.

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