Abstract
Test procedures for detection of a change in the distribution of a sequence of independent observations based on empirical characteristic functions are developed and their limit properties are studied. Theoretical results are accompanied by a simulation study.
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References
Antoch J, Hušková M (2001) Permutation tests for change point analysis. Stat Probab Lett 53:37–46
Antoch J, Hušková M, Jarušková D (2001) Off-line quality control. In: Lauro NC et al. (eds) Multivariate total quality control: foundation and recent advances. Springer, Berlin Heidelberg New York, pp 1–86
Chow YS, Teicher H (1988) Probability theory. Springer, Berlin Heidelberg, New York
Csörgő M, Horváth L (1997) Limit theorems in change-point analysis. J. Wiley, New York
Csörgő S (1985a) Testing for independence by the empirical characteristic function. J Multiv Anal 16:290–299
Csörgő S (1985b) Testing for linearity. Stat Probab Lett 3:45–49
de la Peňa VH, Giné E (1999) Decoupling. From dependence to independence. Springer, Berlin Heidelberg New York
Epps T, Pulley L (1983) A test for normality based on the empirical characteristic function. Biometrika 70:723–726
Epps T (1999) Limit behaviour of the ICF test for normality under Gram–Charlier alternatives. Stat Probab Lett 42:175–184
Heathcote CR (1972) A test for goodness of fit for symmetric random variables. Aust J Stat 14:172–181
Hušková M (2003) Permutation principle and bootstrap in change point analysis. In: Horváth L, Szyszkowicz B (eds) Asymptotic methods in stochastics, vol 44. Fields Institute Communications, pp 273– 291
Gürtler N, Henze N (2000) Goodness–of–fit tests for the Cauchy distribution based on the empirical characteristic function. Ann Inst Stat Math 52:267–286
Kankainen A, Ushakov NG (1998) A consistent modification of a test for independence based on the empirical characteristic function. J Math Sci 89:1486–1494
Koutrouvelis IA (1980a) Regression–type estimation of the parameters of stable laws. J Amer Stat Assoc 75:918–928
Koutrouvelis IA (1980b) A goodness of fit test for simple hypotheses based on the empirical characteristic function. Biometrika 67:238–240
Koutrouvelis IA, Meintanis S (1999) Testing for stability based on the empirical characteristic function with applications to financial data. J Stat Comput Simul 64:275–300
Lehmann EL (1991) Testing statistical hypotheses. Wadsworth & Brooks/Cole, California
Meintanis S (2005) Permutation tests for homogeneity based on the empirical characteristic function. J Nonparametric Stat 17: 583–592
Press SJ (1972) Estimation in univariate and multivariate stable distributions. J Amer Stat Assoc 67:842–846
Serfling R (1980) Approximation theorems of mathematical statistics. Wiley, New York
Ushakov NG (1999) Selected topics in characteristic functions. VSP, Utrecht
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The work of the first author was partially supported by grants GAČR 201/03/0945 and MSM 113200008
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Hušková, M., Meintanis, S.G. Change Point Analysis based on Empirical Characteristic Functions. Metrika 63, 145–168 (2006). https://doi.org/10.1007/s00184-005-0008-9
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DOI: https://doi.org/10.1007/s00184-005-0008-9