Two- and Multi-dimensional Curve Fitting using Bayesian Inference

Andrew W. Steiner

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arXiv · 1802.05339

Two- and Multi-dimensional Curve Fitting using Bayesian Inference

Andrew W. Steiner

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Abstract

Fitting models to data using Bayesian inference is quite common, but when each point in parameter space gives a curve, fitting the curve to a data set requires new nuisance parameters, which specify the metric embedding the one-dimensional curve into the higher-dimensional space occupied by the data. A generic formalism for curve fitting in the context of Bayesian inference is developed which shows how the aforementioned metric arises. The result is a natural generalization of previous works, and is compared to oft-used frequentist approaches and similar Bayesian techniques.

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Andrew W. Steiner. 2018-02-14. Two- and Multi-dimensional Curve Fitting using Bayesian Inference. https://arxiv.org/abs/1802.05339

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