A Semiparametric Tilt Optimality Model

Practitioners often face the situation of comparing any set k distributions, which may follow neither normality nor equality variances. We propose a semiparametric model to compare those distributions using an exponential tilt method. This extends classical analysis variance models when all are unknown by relaxing its assumptions. The proposed is optimal one known. Large-sample estimates parameters derived, and hypotheses for tested one-at-a-time simultaneous comparison cases. Real data examples from NASA meteorology experiments social credit card limits analyzed illustrate our approach. approach shown be preferable in simulated power with existing parametric nonparametric methods.