Bastürk, N.

candidate distribution density likelihood student-t estimator model mixture method estimators adaptive student-t distributions estimate kernel data analysis kernel evaluations evaluation analysis approach sampling estimation candidate distribution target number section ardia statistic choice parameter error student-t distribution importance adaptive student-t candidate chain algorithm candidate distributions efficiency cj estimators combination carlo monte table candidate density result simulation journal regression bridge ris estimator target density transformation shape warp 1 transformation likelihood estimation aus ín independence sequence estimator sample value bayesian probability monte carlo estimators parameter space θ deviation non-elliptical garch 1010 · ml variance 100 000 warp 1 method warp 1 adaptive student-t griddy –gibbs sampler adaptive mixture interval hoogerheide order density kernel function importance density