Summary: The bootstrap was resulted an useful method in estimating the distribution of an estimator or a test statistic by resampling the data in the case of independent and identically distributed observations. Although it was not as efective in the case of dependent data as in the case of independent and identically distributed data, an adaptation was obtained using the block bootstrap. The block bootstrap consist in dividing the data into blocks of observations and then resampling these blocks with replacement. Several block bootstrap methods were proposed, using overlapping blocks or nonoverlapping blocks. When resampling periodic data, we must take in consideration the periodicity present. The traditional block bootstrap procedures do not give the pretended results. With intention to take in consideration the periodicity present in the data, different methods were proposed.
In this paper we will use different block bootstrap procedures in our simulation of periodic data, with intention to make a simulation comparison of the performance of these block bootstrap procedures.