Estimating small signals by using maximum likelihood and Poisson statistics

Hannam, Mark ORCID: https://orcid.org/0000-0001-5571-325X and Thompson, William J. 1999. Estimating small signals by using maximum likelihood and Poisson statistics. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 431 (1-2) , pp. 239-251. 10.1016/S0168-9002(99)00269-7

Full text not available from this repository.

Abstract

Estimation of small signals from counting experiments with backgrounds larger than signals is solved using maximum likelihood estimation for situations in which both signal and background statistics are Poissonian. Confidence levels are discussed, and Poisson, Gauss and least-squares fitting methods are compared. Efficient algorithms that estimate signal strengths and confidence levels are devised for computer implementation. Examples from simulated data and a low count rate experiment in nuclear physics are given.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Physics and Astronomy
Subjects:	Q Science > QB Astronomy
Uncontrolled Keywords:	Upper limit; Confidence intervals; Maximum likelihood; Poisson statistics; Gaussian distribution; Least squares
Publisher:	Elsevier
ISSN:	0168-9002
Last Modified:	20 Oct 2022 08:23
URI:	https://orca.cardiff.ac.uk/id/eprint/28134

Citation Data

Cited 51 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item