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2004 | 24 | 2 | 151-181
Tytuł artykułu

Some remarks on permutation type tests in linear models

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The paper discusses applications of permutation arguments in testing problems in linear models. Particular attention will be paid to the application in L₁-test procedures. Theoretical results will beaccompanied by a simulation study.
Twórcy
  • Charles University of Prague, Department of Statistics, Sokolovská 83, CZ - 186 75 Praha 8, Czech Republic
  • UTIA Czech Academy of Sciences, Czech Republic
autor
  • Technical University of Liberec, Department of Applied Mathematics, Hálkova 6, CZ-461 17 Liberec, Czech Republic
Bibliografia
  • [1] J. Antoch and M. Husková, Detection of structural changes in regression, Tatra Mountains Publications 26 (2003), 201-215.
  • [2] B.M. Brown and J.S. Maritz, Distribution-free methods in regression, Australian Journal of Statistics 24 (1982), 318-331.
  • [3] B.S. Cade and J.D. Richards, Permutation tests for least absolute deviation regression, Biometrics 52 (1996), 886-902.
  • [4] D. De Angelis, P. Hall and G.A. Young, Analytical and bootstrap approximations to estimators in l1 regression, Journal of the American Statistical Association 88 (1993), 1310-1316.
  • [5] D. Edwards, Exact simulation-based inference: A survey, with additions, Journal of Statistical Computation and Simulation 22 (1985), 307-326.
  • [6] B, Efron and R.J. Tibshirani, An Introduction to the Bootstrap, Chapman and Hall, New York 1993.
  • [7] P. Good, Permutation Tests, Springer Verlag, New York 1994.
  • [8] J. Hájek, Some extensions of the Wald-Wolfowitz-Noether theorem, Annals of Mathematical Statistics 32 (1961), 506-523.
  • [9] M. Husková, The rate of convergence of simple linear rank statistics, Annals of Statistics 5 (1977), 658-670.
  • [10] M. Husková, Permutation principle and bootstrap in change point analysis, Asymptotic Methods in Stochastics. Fields Institute Communications, eds. L. Horváth and B. Szyszkowicz 44 pp, 273-292.
  • [11] M. Husková and J. Picek, M-tests for detection of structural changes in regression, Statistical Data Analysis Based on the L₁-Norm and RelatedMethods, ed. Y. Dodge, Birhäuser, Basel (2002), 213-229.
  • [12] P.E. Kennedy, Randomization tests in econometrics, Journal of business and Economic Statistics 13 (1995), 85-94.
  • [13] R. Koenker and G. Basset, Tests of linear hypotheses and L₁- regression, Econometrica 50 (1982), 1577-1583.
  • [14] E.L. Lehmann, Theory of Point Estimation, Wadworth & Brooks/Cole, California 1991.
  • [15] B.F.J. Manly, Randomization and Monte-Carlo Methods in Biology, London: Chapman and Hall 1991.
  • [16] D.N. Politis, J.P. Romano and M. Wolf, Subsampling, Springer Verlag, New York 1999.
  • [17] C.J.F. ter Braak, Permutations versus bootstrap significance in multiple regression and ANOVA, Bootstrapping and Related Techniques, eds. K.H. Jockel, G. Rotheand W. Sendler, Berlin-Springer-Verlag (1992), 79-86.
  • [18] Shao Jun and Tu Dongsheng, The Jackknife and Bootstrap, Springer Verlag, New York 1995.
  • [19] W.J. Welsh, Construction of permutation tests, Journal of the AmericanStatistical Association 85 (1990), 693-689.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.bwnjournal-article-doi-10_7151_dmps_1051
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