High Energy Physics - Phenomenology
[Submitted on 14 Jun 2007 (v1), last revised 25 Oct 2007 (this version, v2)]
Title:Analysis and packaging of radiochemical solar neutrino data. 1. Bayesian approach
View PDFAbstract: According to current practice, the results of each run of a radiochemical solar neutrino experiment comprise an estimate of the flux and upper and lower error estimates. These estimates are derived by a maximum-likelihood procedure from the times of decay events in the analysis chamber. This procedure has the following shortcomings: (a) Published results sometimes include negative flux estimates. (b) Even if the flux estimate is non-negative, the probability distribution function implied by the flux and error estimates will extend into negative territory; and (c) The overall flux estimate derived from the results of a sequence of runs may differ substantially from an estimate made by a global analysis of all of the timing data taken together. These defects indicate that the usual packaging of data in radiochemical solar neutrino experiments provides an inadequate summary of the data, which implies a loss of information. This article reviews this problem from a Bayesian perspective, and suggests an alternative scheme for the packaging of radiochemical solar neutrino data, which is we believe free from the above objections.
Submission history
From: Peter A. Sturrock [view email][v1] Thu, 14 Jun 2007 20:28:26 UTC (43 KB)
[v2] Thu, 25 Oct 2007 18:19:11 UTC (984 KB)
Current browse context:
hep-ph
References & Citations
Bibliographic and Citation Tools
Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)
Code, Data and Media Associated with this Article
alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)
Demos
Recommenders and Search Tools
Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)
IArxiv Recommender
(What is IArxiv?)
arXivLabs: experimental projects with community collaborators
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.
Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.