Bootstrap confidence regions in multinomial sampling

Power divergences can be used to give a measure of distance between two probability vectors. In multinomial sampling arguments can be substituted by empirical and theoretical proportions to obtain confidence regions of parameters. In this paper the bootstrap versions of these confidence regions are constructed. Monte Carlo simulation experiments are carried out to calculate average coverage probabilities and to compare the behavior of the introduced procedures.