2012
DOI: 10.1088/0004-637x/748/2/83
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Model Selection for Spectropolarimetric Inversions

Abstract: Inferring magnetic and thermodynamic information from spectropolarimetric observations relies on the assumption of a parameterized model atmosphere whose parameters are tuned by comparison with observations. Often, the choice of the underlying atmospheric model is based on subjective reasons. In other cases, complex models are chosen based on objective reasons (for instance, the necessity to explain asymmetries in the Stokes profiles) but it is not clear what degree of complexity is needed. The lack of an obje… Show more

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Cited by 18 publications
(5 citation statements)
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“…We identified the pixels whose He I Stokes profiles are better represented by multiple atmosphere components using the Milne-Eddington model (HELIX + ) to fit oneand two-component model fits to the Stokes I and V spectra alone. We applied the Bayesian information criterion for model selection (see Asensio Ramos et al, 2012) and found that less than one percent of the profiles in the observed region needs to be fit with multicomponent atmospheres. We did not perform more fits of the these pixels and eliminated them from the remaining analysis.…”
Section: Multimodel Inversionsmentioning
confidence: 99%
“…We identified the pixels whose He I Stokes profiles are better represented by multiple atmosphere components using the Milne-Eddington model (HELIX + ) to fit oneand two-component model fits to the Stokes I and V spectra alone. We applied the Bayesian information criterion for model selection (see Asensio Ramos et al, 2012) and found that less than one percent of the profiles in the observed region needs to be fit with multicomponent atmospheres. We did not perform more fits of the these pixels and eliminated them from the remaining analysis.…”
Section: Multimodel Inversionsmentioning
confidence: 99%
“…Each fibril is fit to an appropriately ordered polynomial selected according to the Bayesian Information Criterion (Schwarz 1978;Asensio Ramos et al 2012):…”
Section: Fibril Tracingmentioning
confidence: 99%
“…We refer the reader to Del Toro Iniesta and Martínez Pillet (2012) for a discussion on polarimetric accuracy and signal-to-noise ratio. For Bayesian selection among model atmospheres, see Asensio Ramos et al (2012).…”
Section: Degrees Of Approximation In the Model Atmospheresmentioning
confidence: 99%
“…The educated successive sampling grows linearly with the number of free parameters instead of exponentially. The decrease in computational cost has allowed the authors to deal both with ME atmospheres and with general LTE atmospheres where the physical quantities vary with depth (Asensio Ramos et al, 2012).…”
Section: Bayesian Inversionsmentioning
confidence: 99%
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