Work

The Nested_fit Data Analysis Program

Year: 2019

Type: conference-paper

Abstract: 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.

Source: International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt)

DOI: 10.3390/proceedings2019033014

Author: Martino Trassinelli

Institutions: Centre National de la Recherche Scientifique, Sorbonne Université, Institut des NanoSciences de Paris

Language: English

Topic: Markov Chains and Monte Carlo Methods

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: hybrid

Funder: Alexander von Humboldt-Stiftung

OpenAlex ID: W2966597643

FWCI: 3.104

Cites: 22

Cited by: 17

Related to: 10