In this paper, we give sufficient conditions to establish central limit theorems and moderate deviation principle for a class of support estimates of empirical and Poisson point processes. The considered estimates are obtained by smoothing some bias corrected extreme values of the point process. We show how the smoothing permits to obtain gaussian asymptotic limits and therefore pointwise confidence intervals. Some unidimensional and multidimensional examples are provided.
Mots clés : functional estimate, central limit theorem, moderate deviation principles, extreme values, shape estimation
@article{PS_2008__12__273_0, author = {Menneteau, Ludovic}, title = {Multidimensional limit theorems for smoothed extreme value estimates of point processes boundaries}, journal = {ESAIM: Probability and Statistics}, pages = {273--307}, publisher = {EDP-Sciences}, volume = {12}, year = {2008}, doi = {10.1051/ps:2007039}, mrnumber = {2404032}, language = {en}, url = {http://www.numdam.org/articles/10.1051/ps:2007039/} }
TY - JOUR AU - Menneteau, Ludovic TI - Multidimensional limit theorems for smoothed extreme value estimates of point processes boundaries JO - ESAIM: Probability and Statistics PY - 2008 SP - 273 EP - 307 VL - 12 PB - EDP-Sciences UR - http://www.numdam.org/articles/10.1051/ps:2007039/ DO - 10.1051/ps:2007039 LA - en ID - PS_2008__12__273_0 ER -
%0 Journal Article %A Menneteau, Ludovic %T Multidimensional limit theorems for smoothed extreme value estimates of point processes boundaries %J ESAIM: Probability and Statistics %D 2008 %P 273-307 %V 12 %I EDP-Sciences %U http://www.numdam.org/articles/10.1051/ps:2007039/ %R 10.1051/ps:2007039 %G en %F PS_2008__12__273_0
Menneteau, Ludovic. Multidimensional limit theorems for smoothed extreme value estimates of point processes boundaries. ESAIM: Probability and Statistics, Tome 12 (2008), pp. 273-307. doi : 10.1051/ps:2007039. http://www.numdam.org/articles/10.1051/ps:2007039/
[1] The median of the Poisson distribution. Metrika 61 3 (2005) 337-346. | MR | Zbl
and ,[2] A new geometric discriminant rule. Comput. Stat. Q. 2 (1985) 15-30. | Zbl
and ,[3] Convergence of Probability measures. Wiley (1968). | MR | Zbl
,[4] Measuring Labor Efficiency in Post Offices, in The Performance of Public Enterprises: Concepts and Measurements, M. Marchand, P. Pestieau and H. Tulkens Eds., North Holland, Amsterdam (1984).
, and ,[5] Large Deviations. Pure and Applied Mathematics, 137. Boston, MA Academic Press (1989). | MR | Zbl
and ,[6] Detection of abnormal behavior via non parametric estimation of the support. SIAM J. Appl. Math. 38 (1980) 448-480. | MR | Zbl
and ,[7] Large Deviations Techniques and Applications. Jones and Bartlett, Boston and London (1993). | MR | Zbl
and ,[8] Estimating the support of a Poisson process via the Faber-Schauder basis and extrems values. Publications de l'Institut de Statistique de l'Université de Paris XLVI 43-72 (2002). | MR | Zbl
,[9] Sur un problème d'estimation géométrique. Publications de l'Institut de Statistique de l'Université de Paris XIII (1964) 191-200. | MR | Zbl
,[10] On estimation of monotone and concave frontier functions. J. Amer. Statist. Assoc. 94 (1999) 220-228. | MR | Zbl
, , and ,[11] Projection estimates of point processes boundaries. J. Statist. Planning Inference 116 (2003), 1-15. | MR | Zbl
and ,[12] Extreme values and kernel estimates of point processes boundaries. ESAIM: PS 8 (2005) 150-168 . | Numdam | MR | Zbl
and ,[13] Central limit theorems for smoothed extreme value estimates of Poisson point processes boundaries. J. Statist. Planning Inference 135 (2005) 433-460. | MR | Zbl
and ,[14] Smoothed extreme value estimators of non uniform boundaries with applications to star-shaped supports estimation. Submitted.
and ,[15] Une nouvelle approche des problèmes de classification automatique. Statist. Anal. Données 7 (1982) 41-56. | Numdam | MR | Zbl
and ,[16] On the estimation of a support curve of indeterminate sharpness. J. Multivariate Anal. 62 (1997) 204-232. | MR | Zbl
, and ,[17] On polynomial estimators of frontiers and boundaries. J. Multivariate Anal. 66 (1998) 71-98. | MR | Zbl
, and ,[18] Applied nonparametric regression. Cambridge University Press, Cambridge (1990). | MR | Zbl
,[19] Iterated bootstrap with application to frontier models. J. Productivity Anal. 6 (1995) 63-76.
, and ,[20] Estimation of a non sharp support boundaries. J. Multivariate Anal. 43 (1995) 205-218. | Zbl
, and ,[21] Clustering Algorithms. Wiley, Chichester (1975). | MR | Zbl
,[22] Intermediate efficiency theory and examples. Ann. Statist. 11 (1983) 170-182. | MR | Zbl
,[23] On moderate deviation theory in estimation. Ann. Statist. 11 (1983) 498-504. | MR | Zbl
,[24] Efficient estimation of monotone boundaries. Ann. Statist. 23 (1995) 476-489. | MR | Zbl
, and ,[25] Minimax theory of image reconstruction, in Lecture Notes in Statistics 82, Springer-Verlag, New York (1993). | MR | Zbl
and ,[26] Asymptotic efficiency of the estimation of a convex set. Problems Inform. Transmission 30 (1994) 317-327. | MR | Zbl
and ,[27] Asymptotical minimax recovery of sets with smooth boundaries. Ann. Statist. 23 (1995) 502-524. | MR | Zbl
and ,[28] Limit theorems for piecewise constant kernel smoothed estimates of point process boundaries. Technical Report (2007).
,[29] Moderate deviations for the kernel mode estimator and some applications. J. Statist. Planning Inference 135 (2005) 276-299. | MR | Zbl
and ,[30] Limit theorems of probability theory. Sequences of independent random variables. Oxford Studies in Probability, (1995) 4. | MR | Zbl
,[31] Empirical processes with applications to statistics. Wiley, New York (1986). | MR
and ,[32] Fourier series. 2nd ed. New York: Dover Publications (1976). | MR | Zbl
,[33] On nonparametric estimation of density level sets. Ann. Statist. 25 (1997) 948-969. | MR | Zbl
,Cité par Sources :