Uniform strong consistency of a frontier estimator using kernel regression on high order moments
Stéphane Girard; Armelle Guillou; Gilles Stupfler
ESAIM: Probability and Statistics (2014)
- Volume: 18, page 642-666
- ISSN: 1292-8100
Access Full Article
topAbstract
topHow to cite
topGirard, Stéphane, Guillou, Armelle, and Stupfler, Gilles. "Uniform strong consistency of a frontier estimator using kernel regression on high order moments." ESAIM: Probability and Statistics 18 (2014): 642-666. <http://eudml.org/doc/273649>.
@article{Girard2014,
abstract = {We consider the high order moments estimator of the frontier of a random pair, introduced by [S. Girard, A. Guillou and G. Stupfler, J. Multivariate Anal. 116 (2013) 172–189]. In the present paper, we show that this estimator is strongly uniformly consistent on compact sets and its rate of convergence is given when the conditional cumulative distribution function belongs to the Hall class of distribution functions.},
author = {Girard, Stéphane, Guillou, Armelle, Stupfler, Gilles},
journal = {ESAIM: Probability and Statistics},
keywords = {frontier estimation; kernel estimation; strong uniform consistency; Hall class},
language = {eng},
pages = {642-666},
publisher = {EDP-Sciences},
title = {Uniform strong consistency of a frontier estimator using kernel regression on high order moments},
url = {http://eudml.org/doc/273649},
volume = {18},
year = {2014},
}
TY - JOUR
AU - Girard, Stéphane
AU - Guillou, Armelle
AU - Stupfler, Gilles
TI - Uniform strong consistency of a frontier estimator using kernel regression on high order moments
JO - ESAIM: Probability and Statistics
PY - 2014
PB - EDP-Sciences
VL - 18
SP - 642
EP - 666
AB - We consider the high order moments estimator of the frontier of a random pair, introduced by [S. Girard, A. Guillou and G. Stupfler, J. Multivariate Anal. 116 (2013) 172–189]. In the present paper, we show that this estimator is strongly uniformly consistent on compact sets and its rate of convergence is given when the conditional cumulative distribution function belongs to the Hall class of distribution functions.
LA - eng
KW - frontier estimation; kernel estimation; strong uniform consistency; Hall class
UR - http://eudml.org/doc/273649
ER -
References
top- [1] M. Abramovitz and I. Stegun, Handbook of Mathematical Functions. Dover (1965).
- [2] Y. Aragon, A. Daouia and C. Thomas-Agnan, Nonparametric frontier estimation: a conditional quantile-based approach. Econom. Theory21 (2005) 358–389. Zbl1062.62252MR2179542
- [3] N.H. Bingham, C.M. Goldie and J.L. Teugels. Regular Variation. Cambridge, Cambridge University Press (1987). Zbl0667.26003MR898871
- [4] C. Cazals, J.-P. Florens and L. Simar, Nonparametric frontier estimation: a robust approach. J. Econom.106 (2002) 1–25. Zbl1051.62116MR1875525
- [5] A. Daouia and L. Simar, Robust nonparametric estimators of monotone boundaries. J. Multivariate Anal.96 (2005) 311–331. Zbl1077.62021MR2204981
- [6] D. Deprins, L. Simar and H. Tulkens, Measuring labor efficiency in post offices, in The Performance of Public Enterprises: Concepts and Measurements. Edited by P. Pestieau, M. Marchand and H. Tulkens. Amsterdam: North Holland (1984) 243–267.
- [7] U. Einmahl and D.M. Mason, An empirical process approach to the uniform consistency of kernel-type function estimators. J. Theoret. Probab.13 (2000) 1–37. Zbl0995.62042MR1744994
- [8] P. Embrechts, C. Klüppelberg and T. Mikosch, Modelling extremal events. Springer (1997). MR1458613
- [9] L. Gardes and G. Stupfler, Estimation of the conditional tail-index using a smoothed local Hill estimator. Extremes17 (2014) 45–75. Zbl1302.62076MR3179970
- [10] J. Geffroy, Sur un problème d’estimation géométrique. Publ. Inst. Statist. Univ. Paris XIII (1964) 191–210. Zbl0129.32301MR202237
- [11] J. Geffroy, S. Girard and P. Jacob, Asymptotic normality of the L1 −error of a boundary estimator. Nonparametr. Stat. 18 (2006) 21–31. Zbl1096.62048MR2214062
- [12] S. Girard, A. Guillou and G. Stupfler, Frontier estimation with kernel regression on high order moments. J. Multivariate Anal.116 (2013) 172–189. Zbl1277.62111MR3049899
- [13] S. Girard, A. Iouditski and A. Nazin, L1 −optimal nonparametric frontier estimation via linear programming. Autom. Remote Control 66 (2005) 2000–2018. Zbl1267.62048MR2196469
- [14] S. Girard and P. Jacob, Frontier estimation via kernel regression on high power-transformed data. J. Multivariate Anal.99 (2008) 403–420. Zbl1206.62070MR2396971
- [15] S. Girard and P. Jacob, Frontier estimation with local polynomials and high power-transformed data. J. Multivariate Anal.100 (2009) 1691–1705. Zbl1163.62030MR2535380
- [16] P. Hall, On estimating the endpoint of a distribution. Ann. Statist.10 (1982) 556–568. Zbl0489.62029MR653530
- [17] W. Härdle, P. Janssen and R. Serfling, Strong uniform consistency rates for estimators of conditional functionals. Ann. Statist.16 (1988) 1428–1449. Zbl0672.62050MR964932
- [18] W. Härdle and J.S. Marron, Optimal bandwidth selection in nonparametric regression function estimation. Ann. Statist.13 (1985) 1465–1481. Zbl0594.62043MR811503
- [19] W. Härdle, B.U. Park and A. Tsybakov, Estimation of non-sharp support boundaries. J. Multivariate Anal.55 (1995) 205–218. Zbl0863.62030MR1370400
- [20] W. Hoeffding, Probability inequalities for sums of bounded random variables. J. Amer. Statist. Assoc.58 (1963) 13–30. Zbl0127.10602MR144363
- [21] P. Jacob and C. Suquet, Estimating the edge of a Poisson process by orthogonal series. J. Statist. Plann. Inference46 (1995) 215–234. Zbl0834.62075MR1354088
- [22] A. Korostelev, L. Simar and A. Tsybakov, Efficient estimation of monotone boundaries. Ann. Statist.23 (1995) 476–489. Zbl0829.62043MR1332577
- [23] M. Lemdani, E. Ould-Saïd and N. Poulin, Asymptotic properties of a conditional quantile estimator with randomly truncated data. J. Multivariate Anal.100 (2009) 546–559. Zbl1154.62027MR2483437
- [24] Y.P. Mack and B.W. Silverman, Weak and strong uniform consistency of kernel regression estimates. Z. Wahrscheinlichkeitstheorie verw. Gebiete 61 (1982) 405–415. Zbl0495.62046MR679685
- [25] E.A. Nadaraya, On non-parametric estimates of density functions and regression curves. Theory Probab. Appl.10 (1965) 186–190. Zbl0134.36302MR172400
- [26] E. Parzen, On estimation of a probability density function and mode. Ann. Math. Statist.33 (1962) 1065–1076. Zbl0116.11302MR143282
- [27] M. Rosenblatt, Remarks on some nonparametric estimates of a density function. Ann. Math. Statist.27 (1956) 832–837. Zbl0073.14602MR79873
- [28] B.W. Silverman, Weak and strong uniform consistency of the kernel estimate of a density and its derivatives. Ann. Statist.6 (1978) 177–184. Zbl0376.62024MR471166
- [29] W. Stute, A law of the iterated logarithm for kernel density estimators. Ann. Probab.10 (1982) 414–422. Zbl0493.62040MR647513
NotesEmbed ?
topTo embed these notes on your page include the following JavaScript code on your page where you want the notes to appear.