Lognormal selection with applications to lifetime data
We consider selection problems on k lognormal (mu(i), sigma(2)(i)) populations when the sigma(2)(i) are unequal, under both known & unknown cases. Selection based on linear functions of mu & sigma(2)(i) are considered. For the unequal & unknown sigma(2)(i), case, a two-stage Rinott-type asymptotic procedure is proposed. In consideration to reliability & survival analysis applications, an asymptotic procedure is also proposed for the parametric selection based on the alpha-quantiles. Simulation studies to evaluate the procedures & to compare the latter procedure to the nonparametric procedure based on the alpha-quantiles are presented. The procedures are demonstrated using examples from reliability & quality control.
lognormal lifetime data two-stage alpha-quantiles rinott's procedure selection of the best