bootstrap algorithm which is suitable for the dependence case. This allows us to estimate the efficiency percentile confidence …

bootstrap algorithm which is suitable for the dependence case. This allows us to estimate the efficiency percentile confidence …

distribution of the test statistic are studied: an estimation of the asymptotic null distribution and a bootstrap estimator. The …

to approximate it, the bootstrap. We show that the bootstrap yields a consistent distribution estimator. We also study by … simulation the finite sample performance of the bootstrap distribution and compare it with the asymptotic approximation. From the … simulations it can be concluded that it is worth calculating the bootstrap estimator, because it is more accurate than the …

requires the use of a smooth bootstrap procedure to compute critical values. The application of the similarity test to the …

bootstrapping. We show that the bootstrap yields a consistent null distribution estimator. The finite sample performance of the … bootstrap estimator is studied by simulation. We also compare it empirically with the asymptotic null approximation. From the … simulations it can be concluded that it is worth calculating the bootstrap estimator, because it is more accurate than the …

normality which are commonly encountered in business and economic time series. In this article, we explore the bootstrap methods … proposed bootstrap procedures, several macro-economic time series are selected for illustrative purposes. The selected series …

residual CUSUM of squares test (RCUSQ) statistic. The RCUSQ test is based on the bootstrap method introduced to eliminate the …

. This paper proposes to select the bandwidth and kernel order simultaneously by minimizing bootstrap mean squared error for … a plug-in estimator of density weighted averages. We show that standard bootstrap does not work at all for bias … approximation as in density estimation, but smoothed bootstrap is useful in our problem if suitably transformed. …