. In Monte Carlo simulations these tests, and bootstrap ones, generally significantly outperform x squared-based tests. …

Carlo simulations, these tests, and bootstrap tests, generally significantly outperform χ2-based tests. …

asymptotic distribution that is free of nuisance parameters. Secondly, we propose a bootstrap analogue of the transformation and …

This paper studies robustness of bootstrap inference methods for instrumental variable (IV)regression models. We …) estimator introduced by Cížek (2008, 2009),and compare the pairs and implied probability bootstrap approximations for these … statistics byapplying the finite sample breakdown point theory. In particular, we study limiting behaviors ofthe bootstrap …

bootstrap tests based on empirical likelihood for percentiles and expectiles of strictly stationary processes. The percentiles …

sampling variability. It has several advantages over other programs, including the use of microsimulation and the bootstrap … deterministic approach, and may be especially advantageous in investigating distributions of MSLT functions. The bootstrap method …

This paper uses Monte Carlo simulation analysis to study the finite-sample behavior of bootstrap estimators and tests … tailored to handle heteroskedasticity. Our results show that weighted bootstrap methods can be successfully used to estimate … test and of Bartlett and Edgeworth-corrected tests. The bootstrap test was found to be robust against unfavorable …