TY - JOUR
T1 - Asymptotic Sampling Distribution of Inverse Coefficient of Variation and its Applications: Revisited
AU - Albatineh, Ahmad
AU - Kibria, Golam
AU - Zogheib, Bashar
PY - 2014
Y1 - 2014
N2 - Sharma and Krishna (1994) derived mathematically an appealing asymptotic confidence interval for the population signal-to-noise ratio (SNR). In this paper, an evaluation of the performance of this interval using monte carlo simulations using randomly generated data from normal, log-normal, $\chi^2$, Gamma, and Weibull distributions three of which are discussed in Sharma and Krishna (1994). Simulations revealed that its performance, as measured by coverage probability, is totally dependent on the amount of noise introduced. A proposal for using ranked set sampling (RSS) instead of simple random sampling (SRS) improved its performance. It is recommended against using this confidence interval for data from a log-normal distribution. Moreover, this interval performs poorly in all other distributions unless the SNR is around one.
AB - Sharma and Krishna (1994) derived mathematically an appealing asymptotic confidence interval for the population signal-to-noise ratio (SNR). In this paper, an evaluation of the performance of this interval using monte carlo simulations using randomly generated data from normal, log-normal, $\chi^2$, Gamma, and Weibull distributions three of which are discussed in Sharma and Krishna (1994). Simulations revealed that its performance, as measured by coverage probability, is totally dependent on the amount of noise introduced. A proposal for using ranked set sampling (RSS) instead of simple random sampling (SRS) improved its performance. It is recommended against using this confidence interval for data from a log-normal distribution. Moreover, this interval performs poorly in all other distributions unless the SNR is around one.
UR - http://hdl.handle.net/11675/837
U2 - 10.14419/ijasp.v2i1.1475
DO - 10.14419/ijasp.v2i1.1475
M3 - Article
VL - 2
SP - 15
EP - 20
JO - International Journal of Advanced Statistics and Probability
JF - International Journal of Advanced Statistics and Probability
IS - 1
ER -