Gaussfit: Fit Gaussians to Absorption Features of a Normalized Spectrum
In rvmethod: Radial Velocity Method for Detecting Exoplanets

Description Usage Arguments Value Examples

This function takes a spectrum, which ideally is a high signal-to-noise template spectrum estimated with the estimate_template function, and the absorption features found with the findabsorptionfeatures function and uses nonlinear least-squares to fit Gaussians to the features. This follows the procedure described in Holzer et al. (2020).

1	Gaussfit(wvl, flx, ftrs, cores = 1, mse_max1 = 0.00014, mse_max2 = 1e-04)

`wvl`	vector of wavelengths of the spectrum
`flx`	vector of normalized flux of the spectrum
`ftrs`	a list of length 2 vectors that each give the lower and upper bounds of found absorption features. The `wvbounds` component of the `findabsorptionfeatures` function output is designed to be this.
`cores`	the integer count of cores to parallelize over. If set to 1, no parallelization is done.
`mse_max1`	the maximum mean squared error required for a fit from one Gaussian to be considered a good fit for an absorption feature
`mse_max2`	the maximum mean squared error required for a fit of two Gaussians to be considered a good fit for an absorption feature

a list with the following components:

`parameters`	a dataframe with the wavelength bounds, fitted amplitude, fitted center, fitted spread, and fit type for absorption features with a good fit. A fit type of 0 indicates that the feature had a good fit of a single Gaussian. A fit type of 1 indicates that the feature did not have a good fit with a single Gaussian initially, but after fitting with two it did.
`fitted`	the vector of fitted values (with the same length as the `wvl` parameter) using only the features that produced a good fit.
`goodfits`	a vector of the indices for which rows in the `ftrs` parameter were well fitted with either 1 or 2 Gaussians at the end
`mse`	a vector with the mean squared error for each of the features in the `ftrs` parameter using the final fitted values

data(template)
ftrs = findabsorptionfeatures(template$Wavelength,
                              template$Flux,
                              pix_range = 8, gamma = 0.05,
                              alpha = 0.07, minlinedepth = 0.015)
gapp = Gaussfit(template$Wavelength, template$Flux, ftrs)
plot(template$Wavelength, template$Flux)
lines(template$Wavelength, gapp$fitted, col=2)