BECAS
ICAZATTI ZUÑIGA Alejandro Ariel
artículos
Título:
PreliZ: A tool-box for prior elicitation
Autor/es:
ALEJANDRO A ICAZATTI; ORIOL ABRIL-PLA; ARTO KLAMI; MARTIN, OSVALDO A.
Revista:
Journal of open source software
Editorial:
The Journal of Open Source Software
Referencias:
Año: 2023 vol. 8
ISSN:
2475-9066
Resumen:
In a Bayesian modeling workflow, a prior distribution can be chosen in different ways as long as it captures the uncertainty about model parameters prior to observing any data. Particularly, prior elicitation refers to the process of transforming the knowledge of a particular domain into well-defined probability distributions. Here we introduce PreliZ, a Python package aimed at helping practitioners choose prior distributions.
