error distributions. These regression-based variable-addition tests are implemented using asymptotic and bootstrap critical …

to implement the tests using a modified wild bootstrap procedure. The paper theoretically justifies the proposed tests …

that the GDP causes the electricity consumption. The impact multiplier is 0.95 and the long run effect is 0.42. Bootstrap …

A new hybrid model, the wavelet–bootstrap–multiple linear regression (WBMLR) is proposed to explore the potential of … wavelet analysis and bootstrap resampling techniques for daily discharge forecasting. The performance of the developed WBMLR …-based MLR (WMLR), wavelet-based ANN (WANN) and wavelet–bootstrap–ANN (WBANN) models. Seven years of discharge data from seven …

journals in the Database of Research in Science Education (DoRISE), the current study proposes bootstrap methods to estimate … variability estimate differs depending on the way a database selects its journals for inclusion. In the bootstrap process, the … nested structure of articles in a journal was accounted for to ensure that each bootstrap replication reflects the actual …

main contribution is the use of bootstrap methods, which offer more insight into the Feenstra method and can explain why … researchers applying it may tend to find high estimates. The bootstrap not only allows us to obtain considerably less biased …

, the Simar and Wilson procedure is used to bootstrap the data envelopment analysis scores with a truncated regression. …

, residual-based bootstrap methods are introduced for asymptotically refined approximations to the finite sample critical values … conditions are not fully met, bootstrap may lead to unstable critical values that change significantly with the alternative …, whereas when all conditions are met, bootstrap critical values are very stable, approximate much better the finite sample …