TY - JOUR
T1 - An Optimal Sing Test for One-sample Bivariate Location Model Using an Alternative Bivariate Ranked Set Sample
AU - Samawi, Hani M.
AU - Ebrahem, Mohammed Al-Haj
AU - Al-Zubaidin, Noha
AU - Samawi, Hani
PY - 2010/3/1
Y1 - 2010/3/1
N2 - The aim of this paper is to find an optimal alternative bivariate ranked-set sample for one-sample location model bivariate sign test. Our numerical and theoretical results indicated that the optimal designs for the bivariate sign test are the alternative designs with quantifying order statistics with labels {((r + 1)/2, (r + 1)/2)}, when the set size r is odd and {(r/2 + 1, r/2), (r/2, r/2 + 1)} when the set size r is even. The asymptotic distribution and Pitman efficiencies of these designs are derived. A simulation study is conducted to investigate the power of the proposed optimal designs. Illustration using real data with the Bootstrap algorithm for P-value estimation is used.
AB - The aim of this paper is to find an optimal alternative bivariate ranked-set sample for one-sample location model bivariate sign test. Our numerical and theoretical results indicated that the optimal designs for the bivariate sign test are the alternative designs with quantifying order statistics with labels {((r + 1)/2, (r + 1)/2)}, when the set size r is odd and {(r/2 + 1, r/2), (r/2, r/2 + 1)} when the set size r is even. The asymptotic distribution and Pitman efficiencies of these designs are derived. A simulation study is conducted to investigate the power of the proposed optimal designs. Illustration using real data with the Bootstrap algorithm for P-value estimation is used.
KW - Bivariate ranked-set sample
KW - Location model
KW - Median ranked-set sample
KW - Pitman efficiencies
KW - Ranked-set sample
KW - Sign test
KW - Simple random sample
UR - https://digitalcommons.georgiasouthern.edu/biostat-facpubs/150
UR - http://dx.doi.org/10.1080/02664760902810805
U2 - 10.1080/02664760902810805
DO - 10.1080/02664760902810805
M3 - Article
SN - 0266-4763
VL - 37
JO - Journal of Applied Statistics
JF - Journal of Applied Statistics
ER -