Abstract
Section 6.1 provides a discussion about non-random and random censoring. Especially, the sample df is replaced by the Kaplan-Meier estimate in the case of randomly censored data. In Section 6.2 we continue the discussion of Section 2.7 about the clustering of exceedances by introducing time series models and the extremal index. The insight gained from time series such as moving averages (MA), autoregressive (AR) and ARMA series will also be helpful for the understanding of time series like ARCH and GARCH which provide special models for financial time series, see Sections 16.7 and 16.8.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
For relevant results see Balakrishnan, N. and Cohen, A.C. (1991). Order Statistics and Inference. Academic Press, Boston.
See, e.g., Shorack, G.R. and Wellner, J.A. (1986). Empirical Processes with Applications to Statistics. Wiley, New York.
Leadbetter, M.R. and Nandagopalan, S. (1989). On exceedance point processes for stationary sequences under mild oscillation restrictions. In Mikosch, and Resnick, Birkhäuser, Basel [14]}, pp. 69–80.
Chernick, M.R., Hsing, T. and McCormick, W.P. (1991). Calculating the extremal index for a class of stationary sequences. Adv. Appl. Prob. 23, 835–850.
Davis, R.A. and Resnick, S.I. (1985). Limit theory for moving averages of random variables with regular varying tail probabilities. Ann. Prob. 13, 179–195.
Hsing, T., Hüsler, J. and Reiss, R.-D. (1996). The extremes of a triangular array of normal random variables. Ann. Appl. Prob. 6, 671–686.
The basic algorithms are described in Nolan, J.P. (1997). Numerical computation of stable densities and distribution functions. Commun. Statist.-Stochastic Models 13, 759–774. Note that the STABLE package is no longer included in Xtremes.
Nolan, J.P. (1998). Parameterizations and modes of stable distributions. Statist. Probab. Letters 38, 187–195.
Zolotarev, V.M. (1986). One-Dimensional Stable Distributions. Translations of Mathematical Monographs, Vol. 65, American Mathematical Society.
Fofack, H. and Nolan, J.P. (1999). Tail behavior, modes and other characteristics of stable distributions. Extremes 2, 39–58.
McCulloch, J.H. (1986). Simple consistent estimators of stable distribution parameters. Commun. Statist. Simulations 15, 1109–1136.
Kogon, S.M. and Williams, D.B. (1998). Characteristic function based estimation of stable distribution parameters. In: A Practical Guide to Heavy Tails, R.J. Adler et all (eds.), Birkhäuser, Basel, 311–335.
Nolan, J.P. (2001). Maximum likelihood estimation of stable parameters. In: Lévy Processes, ed. by Barndorff-Nielson, Mikosch, and Resnick, Birkhäuser, Basel, 379–400.
Communicated by S. Caserta and C.G. de Vries and stored in blackmarket.dat.
Akgiray, V., Booth, G.G. and Seifert, B. (1988). Distribution properties of Latin American black market exchange rates. J. Int. Money and Finance 7, 37–48.
Koedijk, K.G., Stork, P.A. and Vries, de C.G. (1992). Differences between foreign exchange rate regimes: the view from the tail. J. Int. Money and Finance 11, 462–473.
This condition can be attributed to L. Weiss (1971), see the article cited on page 134.
See, e.g., Goldie, C.M. and Smith, R.L. (1987). Slow variation with remainder term: A survey of the theory and its applications. Quart. J. Math. Oxford Ser. 38, 45–71.
Hall, P. (1982). On estimating the endpoint of a distribution. Ann. Statist. 10, 556–568.
Hall, P. and Welsh, A.H. (1985). Adaptive estimates of parameters of regular variation. Ann. Statist. 13, 331–341.
Kaufmann, E. and Reiss, R.-D. (2002). An upper bound on the binomial process approximation to the exceedance process. Extremes 5, 253–269.
Kaufmann, E. (2000). Penultimate approximations in extreme value theory. Extremes 3, 39–55.
Stored in the file um-lspge.dat (communicated by G.R. Heer, Federal Statistical Office).
Falk, M. and Marohn, F. (1993). Von Mises conditions revisited. Ann. Probab. 21, 1310–1328, and Kaufmann, E. (1995). Von Mises conditions, δ-neighborhoods and rates of convergence for maxima. Statist. Probab. Letters 25, 63–70.
Radtke, M. (1988). Konvergenzraten und Entwicklungen unter von Mises Bedingungen der Extremwerttheorie. Ph.D. Thesis, University of Siegen, (also see, e.g., [42], page 199).
de Haan, L. and Resnick, S.I. (1996). Second order regular variation and rates of convergence in extreme value theory. Ann. Probab. 24, 97–124.
Gomes, M.I. (1984). Penultimate limiting forms in extreme value theory. Ann. Inst. Statist. Math. 36, Part A, 71–85, and Gomes, M.I. (1994). Penultimate behaviour of the extremes. In [15], Vol. 1, 403–418.
Gomes, M.I. and Haan, L. de (1999). Approximation by penultimate extreme value distributions. Extremes 2, 71–85.
Reiss, R.-D. (1989). Extreme value models and adaptive estimation of the tail index. In Mikosch, and Resnick, Birkhäuser, Basel [14]}, 156–165.
Gomes, M.I. (1994). Metodologias Jackknife e Bootstrap em EstatĂstica de Extremos. In Mendes-Lopes et al. (eds.), Actas II Congresso S.P.E., 31–46.
Drees, H. (1996). Refined Pickands estimators with bias correction. Comm. Statist. Theory and Meth. 25, 837–851.
Peng, L. (1998). Asymptotically unbiased estimator for the extreme-value index. Statist. Probab. Letters 38, 107–115.
Martins, M.J., Gomes, M.I. and Neves, M. (1999). Some results on the behavior of Hill estimator. J. Statist. Comput. and Simulation 63, 283–297.
Beirlant, J., Dierckx, G., Gogebeur, Y. and Matthys, G. (1999). Tail index estimation and an exponential regression model. Extremes 2, 177–200.
Feuerverger, A. and Hall, P. (1999). Estimating a tail exponent by modelling departure from a Pareto distribution. Ann. Statist. 27, 760–781.
Gomes, M.I., Martins, M.J. and Neves, M. (2000). Alternatives to a semi-parametric estimator of parameters of rare events-the Jackknife methodology. Extremes 3, 207–229, and Gomes, M.I., Martins, M.J. and Neves, M. (2002). Generalized Jackknife semi-parametric estimators of the tail index. Portugaliae Mathematica 59, 393–408.
Beirlant, J., Vynckier, P. and Teugels, J.L. (1996). Excess function and estimation of the extreme-value index. Bernoulli 2, 293–318.
Fraga Alves, M.I., Gomes, M.I. and de Haan, L. (2003). A new class of semi-parametric estimators of the second order parameter. Portugaliae Mathematica 60, 193–213.
Caeiro, F., Gomes, M.I. and Pestana, D. (2005). Direct reduction of bias of the classical Hill estimator. Revstat 3, 111–136.
Gomes, M.I. and Pestana, D. (2004). A simple second order reduced-bias’ tail index estimator. J. Statist. Comp. and Simulation, in press.
Beirlant, J., Dierckx, G., Guillou, A. and Starica, C. (2002). On exponential representations of log-spacings of extreme order statistics. Extremes 5, 157–180.
Kaufmann, E. and Reiss, R.-D. (1998). Approximation of the Hill estimator process. Statist. Probab. Letters 39, 347–354.
Drees, H., de Haan, L. and Resnick, S.I. (2000). How to make a Hill plot. Ann. Statist. 28, 254–274.
Gomes, M.I. and Martins, M.J. (2002). “Asymptotically unbiased” estimators of the tail index based on external estimation of the second order parameter. Extremes 5, 5–31.
Gomes, M.I., Martins, M.J. and Neves, M. (2005). Revisiting the second order reduced bias “maximum likelihood” extreme value index estimators. Notas e Comunicações CEAUL 10/2005. Submitted.
Gomes, M.I., de Haan, L. and Rodrigues, L. (2004). Tail index estimation through accommodation of bias in the weighted log-excesses. Notas e Comunicações CEAUL 14/2004. Submitted.
Gomes, M.I., Caeiro, F. and Figueiredo, F. (2004). Bias reduction of a tail index estimator through an external estimation of the second order parameter. Statistics 38, 497–510.
Gomes, M.I. and Martins M.J. (2001). Alternatives to Hill’s estimator-asymptotic versus finite sample behaviour. J. Statist. Planning and Inference 93, 161–180.
Fraga Alves, M.I. (2001). A location invariant Hill-type estimator. Extremes 4, 199–217.
Gomes, M.I., Figueiredo, F. and Mendonça, S. (2005). Asymptotically best linear unbiased tail estimators under a second order regular variation condition. J. Statist. Plann. Inf. 134, 409–433
Gomes, M.I., Miranda, C. and Viseu, C. (2006). Reduced bias tail index estimation and the Jackknife methodology. Statistica Neerlandica 60, 1–28.
Rights and permissions
Copyright information
© 2007 Birkhäuser Verlag AG
About this chapter
Cite this chapter
(2007). Advanced Statistical Analysis. In: Statistical Analysis of Extreme Values. Birkhäuser Basel. https://doi.org/10.1007/978-3-7643-7399-3_6
Download citation
DOI: https://doi.org/10.1007/978-3-7643-7399-3_6
Publisher Name: Birkhäuser Basel
Print ISBN: 978-3-7643-7230-9
Online ISBN: 978-3-7643-7399-3
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)