Optimal upper bounds for non-negative parameters
classification
⚛️ physics.data-an
keywords
confidenceboundsintervalslevelnon-negativeoptimalupperarxiv
read the original abstract
Using the techniques of [arXiv:0911.4271], upper bounds for a given confidence level are modified in an optimal fashion to incorporate the a priori information that the parameter being estimated is non-negative. A paradox with different confidence intervals for the same confidence level is clarified. The "lossy compression" nature of the device of confidence intervals is discussed and a "lossless" option to present results is pointed out.
This paper has not been read by Pith yet.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.