Abstract
In a series of papers Beran (1984, 1986, 1988) proposed bootstrap techniques for hypothesis testing. These tests are concerned with the following situation. Let {X 1, X 2,…, X n} be an i.i.d. sample of n random variables with distribution function F and the parameter θ(F) which is a real-valued functional statistic to be tested for H 0: θ(F) = θ 0. To test this hypothesis Beran proposes two alternative approaches. The first one which is called the test statistic approach approximates the exact critical region of the test by the percentiles of its bootstrap distribution, where the unknown distribution of the sample is replaced by its empirical distribution.
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References
Abramovitch, L. and Singh, K. (1985), Edgeworth corrected pivotal statistics and the bootstrap, Ann. Statist., 13, 116–132.
Beran, R. J. (1984), Bootstrap methods in statistics, Jber. der Dt. Math. Verein., 86, 14–30.
Beran, R. J. (1986), Simulated power functions, Ann. Statist., 14, 151–173.
Beran, R. J. (1988) Prepevoting test statistics: A bootstrap view of asymptotic refinements, J. Amer. Statis. Assoc. 83, 687–697.
Efron, B. (1979), Bootstrap methods: Another look at the jackknife. Ann. Statist., 7, 1–26.
Efron, B. (1982), The jackknife, the bootstrap, and other resampling plans, CBMS Monograph #38, Society for Industrial and Applied Mathematics, Philadelphia.
Efron, B. (1987), Better bootstrap confidence interval, J. Amer. Statist. Assoc, 82, 171–185.
Rothe, G. (1986), Some remarks on bootstrap techniques for constructing confidence intervals, Statistische Hefte, 27, 165–172.
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© 1992 Springer-Verlag Berlin Heidelberg
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Breitung, J. (1992). Nonparametric Bootstrap Tests: Some Applications. In: Jöckel, KH., Rothe, G., Sendler, W. (eds) Bootstrapping and Related Techniques. Lecture Notes in Economics and Mathematical Systems, vol 376. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-48850-4_11
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DOI: https://doi.org/10.1007/978-3-642-48850-4_11
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