Confidence intervals for estimating the population signal-to-noise ratio: a simulation study

Florence George and B. M. Golam Kibria

Journal of Applied Statistics, 2012, vol. 39, issue 6, pages 1225-1240

Abstract: This paper considered several confidence intervals for estimating the population signal-to-noise ratio based on parametric, non-parametric and modified methods. A simulation study has been conducted to compare the performance of the interval estimators under both symmetric and skewed distributions. We reported coverage probability and average width of the interval estimators. Based on the simulation study, we observed that some of our proposed interval estimators are performing better in the sense of smaller width and coverage probability and have been recommended for the researchers.

Date: 2012
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