AbstractA comparison between empirical likelihood and bootstrap tests for a mean parameter against a series of local alternative hypotheses is made by developing Edgeworth expansions for the power functions of the two tests. For univariate and bivariate cases, practical rules are proposed for choosing the more powerful test
This paper extends the scope of empirical likelihood methodology in three directions: to allow for p...
Omnibus tests for various nonparametric hypotheses are developed using the empirical likelihood meth...
The small-sample nature of the typical psychophysical experiment presents us with the problem of fin...
AbstractA comparison between empirical likelihood and bootstrap tests for a mean parameter against a...
In this paper we discuss three methods to apply the bootstrap correctly to hypothesis testing. For e...
Many simulation experiments have shown that, in a variety of circumstances, bootstrap tests perform ...
This paper surveys bootstrap and Monte Carlo methods for testing hypotheses in econometrics. Several...
Omnibus tests for various nonparametric hypotheses are developed using the empirical likelihood meth...
The construction of bootstrap hypothesis tests can differ from that of bootstrap confidence interval...
In the independent setting, both Efron's bootstrap and `'empirical Edgeworth expansion'' (E.E-expans...
This paper extends the scope of empirical likelihood methodology in three directions: to allow for p...
Although it is common to refer to “the bootstrap, ” there are actually a great many different bootst...
This paper proposes and analyzes tests that can be used to compare the accuracy of alternative condi...
AbstractPerformance of the bootstrap for estimating tail probabilities is usually explained by sayin...
This paper utilizes the bootstrap to construct tests using the measures for goodness-of-fit for nonn...
This paper extends the scope of empirical likelihood methodology in three directions: to allow for p...
Omnibus tests for various nonparametric hypotheses are developed using the empirical likelihood meth...
The small-sample nature of the typical psychophysical experiment presents us with the problem of fin...
AbstractA comparison between empirical likelihood and bootstrap tests for a mean parameter against a...
In this paper we discuss three methods to apply the bootstrap correctly to hypothesis testing. For e...
Many simulation experiments have shown that, in a variety of circumstances, bootstrap tests perform ...
This paper surveys bootstrap and Monte Carlo methods for testing hypotheses in econometrics. Several...
Omnibus tests for various nonparametric hypotheses are developed using the empirical likelihood meth...
The construction of bootstrap hypothesis tests can differ from that of bootstrap confidence interval...
In the independent setting, both Efron's bootstrap and `'empirical Edgeworth expansion'' (E.E-expans...
This paper extends the scope of empirical likelihood methodology in three directions: to allow for p...
Although it is common to refer to “the bootstrap, ” there are actually a great many different bootst...
This paper proposes and analyzes tests that can be used to compare the accuracy of alternative condi...
AbstractPerformance of the bootstrap for estimating tail probabilities is usually explained by sayin...
This paper utilizes the bootstrap to construct tests using the measures for goodness-of-fit for nonn...
This paper extends the scope of empirical likelihood methodology in three directions: to allow for p...
Omnibus tests for various nonparametric hypotheses are developed using the empirical likelihood meth...
The small-sample nature of the typical psychophysical experiment presents us with the problem of fin...
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