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2,188
Bootstrap Testing In Nonlinear Models
, 1997
"... Bootstrap testing of nonlinear models normally requires at least one nonlinear estimation for every bootstrap sample. We show how to reduce computational costs by performing only a fixed, small number of Newton or quasiNewton steps for each bootstrap sample. The number of steps is smaller for likel ..."
Abstract

Cited by 49 (19 self)
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Bootstrap testing of nonlinear models normally requires at least one nonlinear estimation for every bootstrap sample. We show how to reduce computational costs by performing only a fixed, small number of Newton or quasiNewton steps for each bootstrap sample. The number of steps is smaller
Size Distortion of Bootstrap Tests
"... Bootstrap tests are tests for which the significance level is calculated by some sort of bootstrap procedure, which may be parametric or nonparametric. We provide a theoretical framework in which to study the size distortions of bootstrap P values. We show that, in many circumstances, the size disto ..."
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Cited by 17 (5 self)
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Bootstrap tests are tests for which the significance level is calculated by some sort of bootstrap procedure, which may be parametric or nonparametric. We provide a theoretical framework in which to study the size distortions of bootstrap P values. We show that, in many circumstances, the size
The Size and Power of Bootstrap Tests
"... Bootstrap tests are tests for which the significance level is calculated by some sort of bootstrap procedure, which may be parametric or nonparametric. We show that, in many circumstances, the size distortion of a bootstrap P value for a test will be one whole order of magnitude smaller than that of ..."
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Cited by 2 (1 self)
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Bootstrap tests are tests for which the significance level is calculated by some sort of bootstrap procedure, which may be parametric or nonparametric. We show that, in many circumstances, the size distortion of a bootstrap P value for a test will be one whole order of magnitude smaller than
Improving the Reliability of Bootstrap Tests
"... We rst propose procedures for estimating the rejection probabilities for bootstrap tests in Monte Carlo experiments without actually computing a bootstrap test for each replication. These procedures are only about twice as expensive as estimating rejection probabilities for asymptotic tests. We then ..."
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We rst propose procedures for estimating the rejection probabilities for bootstrap tests in Monte Carlo experiments without actually computing a bootstrap test for each replication. These procedures are only about twice as expensive as estimating rejection probabilities for asymptotic tests. We
Bootstrap tests: How many bootstraps?
 Econometric Reviews
, 2000
"... Abstract In practice, bootstrap tests must use a finite number of bootstrap samples. This means that the outcome of the test will depend on the sequence of random numbers used to generate the bootstrap samples, and it necessarily results in some loss of power. We examine the extent of this power lo ..."
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Cited by 47 (13 self)
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Abstract In practice, bootstrap tests must use a finite number of bootstrap samples. This means that the outcome of the test will depend on the sequence of random numbers used to generate the bootstrap samples, and it necessarily results in some loss of power. We examine the extent of this power
Improving the reliability of bootstrap tests
, 2000
"... Abstract We first propose a procedure for estimating the rejection probabilities for bootstrap tests in Monte Carlo experiments without actually computing a bootstrap test for each replication. This procedure is only about twice as expensive (per replication) as estimating rejection probabilities f ..."
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Cited by 10 (6 self)
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Abstract We first propose a procedure for estimating the rejection probabilities for bootstrap tests in Monte Carlo experiments without actually computing a bootstrap test for each replication. This procedure is only about twice as expensive (per replication) as estimating rejection probabilities
Bootstrap Testing for Fractional Integration ¤
, 1997
"... Asymptotic tests for fractional integration, such as the GewekePorterHudak test, the modi…ed rescaled range test and Lagrange multiplier type tests, exhibit sizedistortions in smallsamples. This paper investigates a parametric bootstrap testing procedure, for sizecorrection, by means of a compu ..."
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Asymptotic tests for fractional integration, such as the GewekePorterHudak test, the modi…ed rescaled range test and Lagrange multiplier type tests, exhibit sizedistortions in smallsamples. This paper investigates a parametric bootstrap testing procedure, for sizecorrection, by means of a
Bootstrap Testing in Nonlinear Models
"... Bootstrap testing of nonlinear models normally requires at least one nonlinear estimation for every bootstrap sample. We show how to reduce computational costs by performing only a fixed, small number of Newton or quasiNewton steps for each bootstrap sample. The number of steps is smaller for likel ..."
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Bootstrap testing of nonlinear models normally requires at least one nonlinear estimation for every bootstrap sample. We show how to reduce computational costs by performing only a fixed, small number of Newton or quasiNewton steps for each bootstrap sample. The number of steps is smaller
SIZE CORRECTED POWER FOR BOOTSTRAP TESTS
, 2000
"... This note provides an alternative perspective for sizecorrected power for a test. The advantage of this approach is that it allows the calculation of sizecorrected power for bootstrap tests. ..."
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This note provides an alternative perspective for sizecorrected power for a test. The advantage of this approach is that it allows the calculation of sizecorrected power for bootstrap tests.
Fast Double Bootstrap Tests
"... It has been shown in previous work that bootstrapping the J test for nonnested linear regression models dramatically improves its nitesample performance. We provide evidence that a more sophisticated bootstrap procedure, which we call the fast double bootstrap, produces a very substantial further ..."
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It has been shown in previous work that bootstrapping the J test for nonnested linear regression models dramatically improves its nitesample performance. We provide evidence that a more sophisticated bootstrap procedure, which we call the fast double bootstrap, produces a very substantial further
Results 1  10
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2,188