A Bayesian inference and model selection algorithm with an optimisation scheme to infer the model noise power
J. Lopez-Santiago,
L. Martino,
J. Miguez
et al.
Abstract:Model fitting is possibly the most extended problem in science. Classical approaches include the use of least-squares fitting procedures and maximum likelihood methods to estimate the value of the parameters in the model. However, in recent years, Bayesian inference tools have gained traction. Usually, Markov chain Monte Carlo methods are applied to inference problems, but they present some disadvantages, particularly when comparing different models fitted to the same dataset. Other Bayesian methods can deal w… Show more
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