The Nested_fit data analysis program

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1. Verfasser: Trassinelli, Martino
Format: Preprint
Veröffentlicht: 2019
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author Trassinelli, Martino
author_facet Trassinelli, Martino
contents We present here Nested_fit, a Bayesian data analysis code developed for investigations of atomic spectra and other physical data. It is based on the nested sampling algorithm with the implementation of an upgraded lawn mower robot method for finding new live points. For a given data set and a chosen model, the program provides the Bayesian evidence, for the comparison of different hypotheses/models, and the different parameter probability distributions. A large database of spectral profiles is already available (Gaussian, Lorentz, Voigt, Log-normal, etc.) and additional ones can easily added. It is written in Fortran, for an optimized parallel computation, and it is accompanied by a Python library for the results visualization.
format Preprint
id arxiv_https___arxiv_org_abs_1907_12259
institution arXiv
publishDate 2019
record_format arxiv
spellingShingle The Nested_fit data analysis program
Trassinelli, Martino
Atomic Physics
Data Analysis, Statistics and Probability
We present here Nested_fit, a Bayesian data analysis code developed for investigations of atomic spectra and other physical data. It is based on the nested sampling algorithm with the implementation of an upgraded lawn mower robot method for finding new live points. For a given data set and a chosen model, the program provides the Bayesian evidence, for the comparison of different hypotheses/models, and the different parameter probability distributions. A large database of spectral profiles is already available (Gaussian, Lorentz, Voigt, Log-normal, etc.) and additional ones can easily added. It is written in Fortran, for an optimized parallel computation, and it is accompanied by a Python library for the results visualization.
title The Nested_fit data analysis program
topic Atomic Physics
Data Analysis, Statistics and Probability
url https://arxiv.org/abs/1907.12259