Closed avivajpeyi closed 2 years ago
NUT sampling is supposedly more robust than nested sampling... but why?
ANS: Checkout this stack exchange: https://stats.stackexchange.com/questions/311813/can-somebody-explain-to-me-nuts-in-english
This apparently works better to fit data when there is more than 1 transit in the data. However not sure of the reasoning for this.
ANS: Sampling is faster w/ gaussian with large sigma -- div is not 0
I know that SPOC does the initial fits -- but how? is it a Bayesian method? or smth more akin to matched-filtering?
Im opening this issue just to help me track some notes, and things I need to look into. This will help with #78 .
useful references
Kipping (2013): for the reparameterization of the limb darkening parameters for a quadratic law, and Luger, et al. (2018): for the light curve calculation (using STARRY) NEMESIS: section 5 has a good description of their MCMC transit model + priors Winn (2014): Transits and Occultations (chapter from textbook) Foreman-Mackey (2017): celerite paper, Section 6.5 Exoplanet Transit Fitting Foreman-Mackey (2016): pop of long period transiting exoplanets (see appdx) Mandel 2002: Analytic lc for transit searches (this is what is used in STARRY)
Papers that cite exoplanet